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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted by number of followers
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 310)
Control Systems     Hybrid Journal   (Followers: 250)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 196)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 192)
Electronics     Open Access   (Followers: 132)
Advances in Electronics     Open Access   (Followers: 126)
Electronic Design     Partially Free   (Followers: 125)
Electronics For You     Partially Free   (Followers: 124)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 117)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 94)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 90)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 88)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 84)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 84)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 82)
IET Power Electronics     Open Access   (Followers: 72)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 67)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 63)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 62)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 58)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 53)
Advances in Power Electronics     Open Access   (Followers: 52)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 52)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 45)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 41)
IET Microwaves, Antennas & Propagation     Open Access   (Followers: 36)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 35)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 33)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 29)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 28)
Electronics Letters     Open Access   (Followers: 28)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 27)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 24)
International Journal of Power Electronics     Hybrid Journal   (Followers: 24)
Journal of Sensors     Open Access   (Followers: 24)
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 22)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 20)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 19)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 18)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 18)
Journal of Artificial Intelligence     Open Access   (Followers: 18)
IET Wireless Sensor Systems     Open Access   (Followers: 17)
Circuits and Systems     Open Access   (Followers: 16)
Machine Learning with Applications     Full-text available via subscription   (Followers: 16)
Archives of Electrical Engineering     Open Access   (Followers: 15)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 14)
International Journal of Control     Hybrid Journal   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 14)
Superconductivity     Full-text available via subscription   (Followers: 13)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 12)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 12)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 12)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 12)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 12)
Advances in Microelectronic Engineering     Open Access   (Followers: 12)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 11)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
Open Journal of Antennas and Propagation     Open Access   (Followers: 11)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 11)
Solid-State Electronics     Hybrid Journal   (Followers: 10)
IETE Journal of Research     Open Access   (Followers: 10)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 10)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 10)
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 9)
IETE Technical Review     Open Access   (Followers: 9)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 9)
Nature Electronics     Hybrid Journal   (Followers: 9)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 8)
Journal of Power Electronics     Hybrid Journal   (Followers: 8)
China Communications     Full-text available via subscription   (Followers: 8)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 8)
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
Batteries     Open Access   (Followers: 8)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 8)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 7)
Metrology and Measurement Systems     Open Access   (Followers: 7)
Nanotechnology, Science and Applications     Open Access   (Followers: 7)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 7)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 6)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
International Journal of Electronics     Hybrid Journal   (Followers: 6)
Energy Storage Materials     Full-text available via subscription   (Followers: 6)
Electronic Markets     Hybrid Journal   (Followers: 6)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 6)
Annals of Telecommunications     Hybrid Journal   (Followers: 6)
Journal of Optoelectronics Engineering     Open Access   (Followers: 5)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 5)
IEEE Pulse     Hybrid Journal   (Followers: 5)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Field Robotics     Hybrid Journal   (Followers: 5)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 5)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 4)
Frontiers in Electronics     Open Access   (Followers: 4)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 4)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Wireless and Mobile Technologies     Open Access   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal   (Followers: 4)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 4)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 4)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Networks: an International Journal     Hybrid Journal   (Followers: 4)
Advanced Materials Technologies     Hybrid Journal   (Followers: 4)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 4)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 3)
Journal of Semiconductors     Full-text available via subscription   (Followers: 3)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Informatik-Spektrum     Hybrid Journal   (Followers: 3)
IETE Journal of Education     Open Access   (Followers: 3)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 3)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 3)
Sensors International     Open Access   (Followers: 3)
Advancing Microelectronics     Hybrid Journal   (Followers: 3)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 3)
e-Prime : Advances in Electrical Engineering, Electronics and Energy     Open Access   (Followers: 3)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 2)
Journal of Information and Telecommunication     Open Access   (Followers: 2)
ACS Applied Electronic Materials     Open Access   (Followers: 2)
Energy Storage     Hybrid Journal   (Followers: 2)
IET Smart Grid     Open Access   (Followers: 2)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal   (Followers: 2)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 2)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Journal of Nuclear Cardiology     Hybrid Journal   (Followers: 2)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 2)
Open Electrical & Electronic Engineering Journal     Open Access   (Followers: 1)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 1)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 1)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access  
npj Flexible Electronics     Open Access  
Elektronika ir Elektortechnika     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
IEEE Solid-State Circuits Letters     Hybrid Journal  
IEEE Open Journal of Industry Applications     Open Access  
IEEE Open Journal of the Industrial Electronics Society     Open Access  
IEEE Open Journal of Circuits and Systems     Open Access  
Journal of Electronic Science and Technology     Open Access  
Solid State Electronics Letters     Open Access  
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Journal of Engineered Fibers and Fabrics     Open Access  
Jurnal Teknologi Elektro     Open Access  
IET Nanodielectrics     Open Access  
Elkha : Jurnal Teknik Elektro     Open Access  
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Jurnal Teknik Elektro     Open Access  
IACR Transactions on Symmetric Cryptology     Open Access  
Acta Electronica Malaysia     Open Access  
Bioelectronics in Medicine     Hybrid Journal  
Chinese Journal of Electronics     Open Access  
Problemy Peredachi Informatsii     Full-text available via subscription  
Technical Report Electronics and Computer Engineering     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access  
Telematique     Open Access  
International Journal of Nanoscience     Hybrid Journal  
International Journal of High Speed Electronics and Systems     Hybrid Journal  

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Similar Journals
Journal Cover
Sensing and Imaging : An International Journal
Journal Prestige (SJR): 0.255
Citation Impact (citeScore): 1
Number of Followers: 2  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1557-2072 - ISSN (Online) 1557-2064
Published by Springer-Verlag Homepage  [2469 journals]
  • Learned Anomaly Detection with Terahertz Radiation in Inline Process
           Monitoring

    • Free pre-print version: Loading...

      Abstract: Abstract Terahertz tomographic imaging as well as machine learning tasks represent two emerging fields in the area of nondestructive testing. Detecting outliers in measurements that are caused by defects is the main challenge in inline process monitoring. An efficient inline control enables to intervene directly during the manufacturing process and, consequently, to reduce product discard. We focus on plastics and ceramics, for which terahertz radiation is perfectly suited because of its characteristics, and propose a density based technique to automatically detect anomalies in the measured radiation data. The algorithm relies on a classification method based on machine learning. For a verification, supervised data are generated by a measuring system that approximates an inline process. The experimental results show that the use of terahertz radiation, combined with the classification algorithm, has great potential for a real inline manufacturing process. In a further investigation additional data are simulated to enlarge the data set, especially the variety of defects. We model the propagation of terahertz radiation by means of the Eikonal equation.
      PubDate: 2022-09-18
       
  • A Novel Non-maximum Suppression Strategy via Frame Bounding Box Smooth for
           Video Aerobics Target Location

    • Free pre-print version: Loading...

      Abstract: Abstract At present, a large number of studies in object detection from video focus on improving the accuracy of location prediction frame, but few studies research the improvement of location stability. However, the location stability of prediction frame has important influence on multi-target tracking and motion recognition etc. In order to improve the aerobics location stability of the prediction frame, a novel non-maximum suppression strategy via frame bounding box smooth is proposed in this paper. In the stage of target detection, spatial pyramid pooling network (SPP-Net) is used. In the stage of non-maximum suppression, results are obtained by integrating information of multiple prediction frames to enhance the stability of prediction frames in continuous video streams. Subsequently, by using the information association of adjacent frames, the prediction frame is smoothed to further improve the positioning stability of the prediction frame. Self-made aerobics data set is selected for analysis experiment, and the results show that the proposed method has greatly improved the location stability, and the corresponding tracking quality has been significantly improved. The mAP of proposed method exceeds 92.6% compared other methods, which has a better effect in object detection area.
      PubDate: 2022-09-02
       
  • Investigation of Sensing Characteristics for the Detection of Formaldehyde
           Using a Multichannel Data Acquisition System and Semiconductor Metal Oxide
           Sensor

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      Abstract: Abstract A multichannel data acquisition setup was designed and developed uniquely for detection of low concentration of formaldehyde using semiconductor metal oxide sensor. The selectivity towards formaldehyde was achieved by choosing optimized temperature of sensor operation. The gas sensing studies proved useful for sensing formaldehyde in the concentration range of 20–100 ppm. The mean and standard deviation of baseline stability of sensor were 14.8 kΩ and 0.21 kΩ respectively.
      PubDate: 2022-08-29
       
  • Carcinogenic Chromium (VI) Sensing Using Transducing Characteristics of
           Fiber Bragg Grating and Physical Swelling of Hydrogel

    • Free pre-print version: Loading...

      Abstract: Abstract A Chemo-mechanical-optical sensing approach for the detection of hexagonal chromium (Cr6+) metal ion is demonstrated. A new sensor head is designed by epoxying fiber Bragg grating (FBG) on a thin silicon membrane beneath which a Chromium (VI) responsive hydrogel is embedded. When the gel is exposed to chromium spiked solutions, it suffers a volume change due to its stimulus responsive property and deforms a silicon membrane which in turn causes a wavelength peak shift of FBG. Hydrogel synthesized from the blends of (3-Acrylamidopropyl)—trimethylammonium chloride is used for the purpose. The relation between FBG peak shifts with change in volume of hydrogel due to it swelling is experimentally established. The FBG wavelength peak shift is directly correlated with the concentration of the Cr (VI) metal ion. The estimated sensitivity and resolution of the sensor are 0.1 nm/ppb with a limit of detection of the sensor is 0.75 ppb. The sensor has demonstrated good sensitivity, selectivity, and repeatability.
      PubDate: 2022-08-05
       
  • Simulation of Optical Hollow Microbottle Resonator for Sensing
           Applications

    • Free pre-print version: Loading...

      Abstract: Abstract A silica hollow microbottle resonator (HMBR) combined with a pair of curved silicon micro-mirrors on the outside wall of the microbottle is proposed and numerically investigated using the Finite-Difference Time-Domain (FDTD) algorithm. The microbottle has only 32 μm length, 26 μm width and 1.5 μm wall thickness. The curved micro-mirrors overcome the light diffraction loss through light focusing, while the microbottle, in which gas analytes are introduced, provides additional light confinement and hence improves the performance of the sensor. The obtained Q-factor is about 4590 at 1543.21 nm and the free spectral range (FSR) is more than 31 nm. An internal sensitivity of 1567 nm per refractive index unit (RIU) is achieved in the near-infrared (NIR), which is the highest ever reported for an refractive index (RI) gas sensor based on HMBR. With the introduction of an air gap layer between the silica HMBR and the silicon micro-mirrors, both the Q-factor and sensitivity have been improved to 6729 and 1730 nmRIU− 1 respectively. We believe that the proposed architecture will be used in future sensing applications.
      PubDate: 2022-08-03
       
  • Correction to: Adaptive Higher‑Order Spectral Analysis for Image
           Recovery Under Distortion of Moving Water Surface Using
           Dragonfly‑Colliding Bodies Optimization

    • Free pre-print version: Loading...

      PubDate: 2022-07-20
      DOI: 10.1007/s11220-022-00393-3
       
  • Motion Capture Sensing Technologies and Techniques: A Sensor Agnostic
           Approach to Address Wearability Challenges

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      Abstract: Abstract Body area sensing systems specifically designed for motion capture need to consider the wearer’s comfort and wearability criteria. In this paper, after studying body models and their approximation by link-segment models, the kinematics and inverse kinematics problems for determining motion are explored. Different sensor technologies and related motion capture systems are then discussed within the context of wearability and portability challenges of the systems. For such systems, the weight and size of the system need to be kept small and the system should not interfere with the user’s movements. The requirements will be considered in terms of portability: portable motion capture systems should be less sensitive in accurate positioning of sensors and have more battery lifetime or less power consumption for their wider adoption as an assisted rehabilitation platform. Therefore, a proposed signal processing technique is validated in a controlled setting to address the challenges. By reducing sampling frequency, the power consumption will be reduced but there would be more variability in data whereas by utilising an adaptive filtering approach the variation can be compensated for. It is shown how by using the technique it is possible to reduce the energy consumption; therefore, the potential to decrease the battery size leading to a less bulky on-body sensing system with more comfort to the wearer.
      PubDate: 2022-07-20
      DOI: 10.1007/s11220-022-00394-2
       
  • Modeling Electrical Resistance Behavior of Soft and Flexible
           Piezoresistive Sensors Based on Carbon-Black/Silicone Elastomer Composites
           

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      Abstract: Abstract Soft and flexible strain piezoresistive sensors are gaining interest in wearable and robotic applications, but resistance relaxation limits the widespread use of the sensors. As soft, flexible, and stretchable sensors, they can easily be retrofitted into any existing robotic hand. To understand the resistance relaxation of stretchable sensors, three different elastomers were used to fabricate soft piezoresistive sensors. The experimental results showed that the sensor has good linearity and scalability while their resistance is strongly influenced by the stretching speed and modulus of the elastomer. Thus, the Kevin Voigt model was adopted to describe the sensor’s change of resistance during the stretching process. The model is sufficient to describe the change of resistance of the carbon black/elastomer filler when the sensors are stretched before the fracturing of the conductive filler. However, when the filler fractures, the model is invalid. The behavior indicates that the elongation of the sensor must not exceed the strain that causes the filler to fracture.
      PubDate: 2022-07-01
      DOI: 10.1007/s11220-022-00392-4
       
  • BI-LSTM Based Encoding and GAN for Text-to-Image Synthesis

    • Free pre-print version: Loading...

      Abstract: Abstract Synthesizing images from text is to produce images with reliable content as specified text depiction that is an extremely demanding task with the most important problems like: content consistency and visual realism. Owing to considerable progression of GAN, it is now possible to produce images with good visual certainty. The translation of text descriptions to images with higher content reliability, on the other hand, is still a work in progress. This paper intends to frame a novel text-to-image synthesis approach, which includes two major phases namely; (1) Text to image encoding and (2) GAN. Initially, during text to image encoding, cross modal feature alignment takes place including text and image features. Consequently, BI-LSTM is deployed to transfer the text embedding to feature vector. At second stage, the image is synthesized based on the encoding. Consequently, text feature group are given as input to GAN, which offers the final synthesized images. Finally, the supremacy of developed approach is examined via evaluation over extant techniques.
      PubDate: 2022-07-01
      DOI: 10.1007/s11220-022-00390-6
       
  • Efficient Multi-focus Image Fusion Using Parameter Adaptive Pulse Coupled
           Neural Network Based Consistency Verification

    • Free pre-print version: Loading...

      Abstract: Abstract Multi-focus image fusion technique is an important approach to generate a composite image with all objects in focus. Accurate focused pixel detection from multiple source images is crucial for multi-focus image fusion. However, false detection of focused pixels is inevitably due to the low-level image features being usually used to achieve focus pixel classification in most fusion methods. Consistency verification operation is frequently used to revise the falsely detected focused pixels in many fusion schemes. However, most consistency verification strategies cannot achieve the desired results. In this paper, we modify the parameter adaptive pulse coupled neural network (PA-PCNN) by introducing a new strategy to measure the linking strength of neurons. Thus, the PA-PCNN can greatly improve the accuracy of identifying focused pixels. The proposed method contains four steps. Firstly, the residual between an image and its filtered version by efficient mean filter is used to calculate the sharpness of a source image. Then, a new consistency verification method based on adaptive pulse coupled neural network (PA-PCNN) is adopted to improve the accuracy of the initial sharpness. Next, the focus detection maps are constructed by comparing the refined sharpness of two source images. Finally, the fused image is constructed according to the focus detection map. Experimental results show that the proposed method has achieved comparable or even better results compared with the state-of-the-art approaches in both visual quality and objective evaluation.
      PubDate: 2022-06-29
      DOI: 10.1007/s11220-022-00391-5
       
  • Floating Point Implementation of the Improved QRD and OMP for Compressive
           Sensing Signal Reconstruction

    • Free pre-print version: Loading...

      Abstract: Abstract In this paper, the Floating-Point Core Architecture based QR decomposition is proposed for solving least square problems in the Orthogonal Matching Pursuit algorithm (OMP-FPCA-QRD). To improve the computational performance of Orthogonal Matching Pursuit (OMP), it is necessary to modify the Orthogonal Matching Pursuit algorithm for analysing a wide range of signals in field programmable gate array (FPGA). As a result, it highly benefits from the available resources and acquires a scalable computational complexity. Since the solution of least square problem involves some iterative parts, like square root and division units, the processing time of the proposed QR Decomposition (QRD) approach is decreased by increasing parallelism using processing element driven systolic array implementation across all data-dependent operations. The hardware implementation on the ALTERA field programmable gate array shows optimal performance depends on hardware complexity and frequency of operation with the improved computational accuracy over existing QR Decomposition implementations. Moreover, the implementation of Orthogonal Matching Pursuit algorithm for signal reconstruction is also proposed to validate the performance metrics of floating point unit (FPU). The experimental results show that the optimization of floating point unit offers significant resource optimization in QR decomposition, and also better performance of high peak signal-to-noise ratio of 32.99 dB, which outperforms all other fixed point Orthogonal Matching Pursuit systems.
      PubDate: 2022-06-26
      DOI: 10.1007/s11220-022-00389-z
       
  • Adaptive Higher-Order Spectral Analysis for Image Recovery Under
           Distortion of Moving Water Surface using Dragonfly-Colliding Bodies
           Optimization

    • Free pre-print version: Loading...

      Abstract: Abstract Reconstruction of an underwater object from a sequence of images distorted by moving water waves is a challenging task. Most of the environmental research has been employing image data in recent days. The precision of this research is often dependent on the superiority of image data. In the existing approaches, the problem of analyzing video sequences when the water surface is disturbed by waves. The water waves will affect the appearance of the individual video frames such that no single frame is completely free of geometric distortion. Thus, the image acquisition from the environmental condition is more complex and crucial, but it must be focused on getting the high spectral and spatial quality. The primary intent of this paper is to plan for the intelligent higher-order spectral analysis for recovering the images from the moving water surface. The three main phases of the proposed image recovery model are (a) image pre-processing, (b) lucky region selection, and (c) image recovery. Once the pre-processing of the image is carried out, the lucky region selection is performed by computing the dice coefficient method. As a modification to the existing methods, the proposed model adopts optimized bispectra to enhance the quality of the recovered image. A hybrid algorithm with Dragonfly-Colliding Body Optimization (D-CBO) is used for enhancing the bispectra method. The proposed model has been tested on distorted underwater images. From the experimental analysis, in terms of PSNR measure, the suggested D-CBO-bispectra gets better efficiency than other conventional models, in which D-CBO-bispectra is 10.7%, 8.7%, 19%, 6.8% and 5% progressed than Blind deconv, Bispectra, Bispectra with Fourier, and Radon transform, respectively. Finally, the comparison of the proposed model with the existing approaches proves the method's efficiency.
      PubDate: 2022-05-17
      DOI: 10.1007/s11220-022-00388-0
       
  • Electric Resistance Tomograph (ERT): a review as non-destructive Tool
           (NDT) in deciphering interiors of standing trees

    • Free pre-print version: Loading...

      Abstract: Abstract The Electric Resistance Tomograph (ERT) is a customized tree specific novel German-technology which was developed to monitor and estimate the tree growth development by looking into the inner structure of the tree to analyse the growth and health status. This technique contributes to detect and study the internal assembly of a tree for the mapping of decay, hollowness, and also to distinguish the sapwood and heartwood demarcation, this way of discovering the internal growth at an early stage, mainly for the timber trees which are economically important can help to regulate thereafter to check whether the growth is not hindered. This paper highlights the device operational methods, electric resistance testing of trees and its applications, also reviewed the various successful application of this equipment in various tree species through-out the world to estimate non-destructively for accurate quantification of standing trees. The performance of this instrument has created breakthrough among various studies and methodologies to spot the internal condition in a standing tree with less invasive ways.
      PubDate: 2022-05-11
      DOI: 10.1007/s11220-022-00385-3
       
  • A Dynamic Image Encryption Algorithm Based on Improved Ant Colony Walking
           Path Thought

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      Abstract: Abstract According to the existing chaotic image encryption technology, this paper designs an algorithm based on the thought of improved ant colony walking path to encrypt the image. In this paper, the key is generated using SHA-512, and the required chaotic sequence is generated using the PWLCM one-dimensional chaotic system. First, the image is scrambled by the row and column indexes by the improved algorithm so that complete the first scrambling. Then, the image is converted into one-dimensional array, and randomly scrambled according to the designed algorithm. Finally, the one-dimensional array is divided into two segments with the middle point serving as the boundary, and each segment is created using distinct rules based on the array’s number and parity to complete the diffusion, after which the array is restored to its original size. Simulation results show that this algorithm has better performance and robustness in encryption compared with other algorithms.
      PubDate: 2022-05-03
      DOI: 10.1007/s11220-022-00387-1
       
  • DSSEMFF: A Depthwise Separable Squeeze-and-excitation Based on
           Multi-feature Fusion for Image Classification

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      Abstract: Abstract Image classification refers to the classification of the input image according to some algorithms. The general steps of image classification include image preprocessing, image feature extraction and image classification judgment. Convolutional neural network (CNN) imitates the visual perception mechanism of biology, solves the complicated engineering of traditional manual feature extraction, and realizes automatic feature extraction from data. However, CNN still has the disadvantages of low efficiency and incomplete feature extraction. In this paper, we propose a depthwise separable squeeze-and-excitation based on multi-feature fusion (DSSEMFF) for image classification. Through feature fusion of multiple models, the network can learn the input features with different levels of images, increase feature complementarity and improve feature extraction ability. By adding the attention module, the network can pay more attention to the targeted area and reduce irrelevant background interference information. Finally, we conduct experiments with other state-of-the-art classification methods, the accuracy is higher than 90% and the error rate is lower than 18% the results show that the effectiveness of the proposed method obtains the better effect.
      PubDate: 2022-05-03
      DOI: 10.1007/s11220-022-00383-5
       
  • Quality of Experience Evaluation Model with No-Reference VMAF Metric and
           Deep Spatio-temporal Features of Video

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      Abstract: Abstract For mobile streaming media service providers, it is necessary to accurately predict the quality of experience (QoE) to formulate appropriate resource allocation and service quality optimization strategies. In this paper, a QoE evaluation model is proposed by considering various influencing factors (IFs), including perceptual video quality, video content characteristics, stalling, quality switching and video genre attribute. Firstly, a no-reference video multimethod assessment fusion (VMAF) model is constructed to measure the perceptual quality of the video by the deep bilinear convolutional neural network. Then, the deep spatio-temporal features of video are extracted using a TSM-ResNet50 network, which incorporates temporal shift module (TSM) with ResNet50, obtaining feature representation of video content characteristics while balancing computational efficiency and expressive ability. Secondly, video genre attribute, which reflects the user’s preference for different types of videos, is considered as a IF while constructing the QoE model. The statistical parameters of other IFs, including the video genre attribute, stalling and quality switching, are combined with VMAF and deep spatio-temporal features of video to form an overall description parameters vector of IFs for formulating the QoE evaluation model. Finally, the mapping relationship model between the parameters vector of IFs and the mean opinion score is established through designing a deep neural network. The proposed QoE evaluation model is validated on two public video datasets: WaterlooSQoE-III and LIVE-NFLX-II. The experimental results show that the proposed model can achieve the state-of-the-art QoE prediction performance.
      PubDate: 2022-04-18
      DOI: 10.1007/s11220-022-00386-2
       
  • SSRNet: A CT Reconstruction Network Based on Sparse Connection and Weight
           Sharing for Parameters Reduction

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      Abstract: Abstract In recent years, the neural networks are frequently adopted to address the issues of cone beam CT imaging. However, most of the research so far has been to build neural networks individually either in the image domain or in the projection domain for specific purposes, while the connections between them are not well exploited. A reconstruction network that focuses on the filtering and backward projection process can fully exploit the potential connections between the projection domain and the image domain, and can be plugged into other learned reconstruction models for high-quality results. However, until now most of the existing reconstruction networks have taken the fully-connected layer as the backbone, which leads to an explosive growth in model parameters, especially in reconstruction of cone-beam CT. In this paper, a sparse-sharing-reconstruction network (SSRNet) with sparse connections and multi-group weight sharing is proposed, which can be regarded as a substitute of the filtering and backward projection process and can significantly reduce the number of network parameters up to 0.4% of that of the previous models. The experimental results show that the reconstruction results of the 2D SSRNet are basically consistent with those of the traditional FBP algorithm. The 3D SSRNet outperforms the traditional FDK algorithm at 50 layers away from the midplane, while still keeping the number of network parameters within a manageable range.
      PubDate: 2022-03-28
      DOI: 10.1007/s11220-022-00384-4
       
  • Optimized Cantilever Sensor Based on Parallel High Dielectric Material

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      Abstract: Abstract Cantilever is dramatically used as a resonator sensor to detect the presence of a particular molecule or cell in an environment and to measure their amount. Electrostatic force is commonly used to actuate MEMS based cantilevers to resonate because a cantilever has a simple capacitor structure. In this paper, a novel design is proposed to optimize the cantilevers performance by use of high dielectric material in its capacitor structure. The mathematical model of the proposed design and the performance of the cantilever sensor and its quality has been evaluated and reported by finite element simulations in this way.
      PubDate: 2022-03-22
      DOI: 10.1007/s11220-022-00381-7
       
  • A Framework for Super Resolution of Color Images with Missing Samples
           Using Low Rank Approximation

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      Abstract: Abstract Images captured from extreme surveillance environments may contain missing pixels because of the damaged sensors and dusty particles including debris from combustion fuels and spider webs. This paper addresses the challenging problem of super resolving color images from low resolution images with missing sample values. In conventional methods, missing pixel estimation and super resolution are carried out separately. Unlike the conventional techniques, the proposed method performs simultaneous missing pixel estimation, super resolution and color reconstruction in a unified framework. The problem is posed in a regularized optimization framework with a suitable objective function. The formulated objective function consists of a weighted data fidelity term to control the contribution from each pixel position, a nuclear norm regularization term for enforcing image completion, a three dimensional total variation term for ensuring edge consistency and a sparsity based color regularization term for enforcing proper color reconstruction. Significance of each terms in the regularization function is studied and the results are presented. Experimental results show that proposed method gives improved performance than the conventional methods in most of the cases.
      PubDate: 2022-03-16
      DOI: 10.1007/s11220-022-00380-8
       
  • A Comparative Analysis of the Algorithms for De-noising Images
           Contaminated with Impulse Noise

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      Abstract: Abstract Image pre-processing is one of the vital tasks used to redefine an image to enhance human visual perception and better information extraction. Several state-of-art have been proposed to de-noise an image contaminated with impulsive noise. This paper focuses on the study and analysis of several de-noising algorithms based on median filter and its advanced non-linear approaches. The study further concentrates on the implementation approaches proposed for de-noising impulsive noise with the deep learning technique. The study highlights the limitation of one approach and its possible solutions with other approaches proposed. The study also highlights several other issues such as optimum selection of window size, edge restoration, even number of noise-free pixels in the median filter, and its variations which have no solution so far. The performance metrics used for the evaluation of several state-of-art algorithms are peak signal-to-noise ratio (PSNR), mean absolute error, computation time and structural similarity index (SSIM). Some of the recently developed algorithms such as classifier and regression model and deep convolutional neural network-based model show PSNR of 45.66 dB and 45.14 dB in 10% noise density and 28.77 dB and 29.18 dB in 90% noise density using Lena image respectively while SSIM of 0.9851 and 0.9847 in 10% noise density and 0.8116 and 0.8101 in 90% noise density using sample1 from BBBC041 dataset respectively. The paper brings out the limitations and issues associated with the conventional and deep learning approaches for the removal of impulsive noise both subjectively and objectively.
      PubDate: 2022-03-11
      DOI: 10.1007/s11220-022-00382-6
       
 
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