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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advanced Materials Technologies     Hybrid Journal   (Followers: 1)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 8)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 9)
Advances in Electronics     Open Access   (Followers: 100)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
Advances in Power Electronics     Open Access   (Followers: 40)
Advancing Microelectronics     Hybrid Journal  
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 28)
Annals of Telecommunications     Hybrid Journal   (Followers: 8)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 16)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal  
Batteries     Open Access   (Followers: 9)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 31)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 309)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 2)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 124)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 109)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 103)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elektronika ir Elektortechnika     Open Access   (Followers: 2)
Elkha : Jurnal Teknik Elektro     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access   (Followers: 3)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage     Hybrid Journal   (Followers: 1)
Energy Storage Materials     Full-text available via subscription   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal  
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 9)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
IACR Transactions on Symmetric Cryptology     Open Access   (Followers: 1)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 102)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 57)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 3)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 52)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 4)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 42)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 3)
IEEE Open Journal of Industry Applications     Open Access   (Followers: 3)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 3)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 77)
IEEE Pulse     Hybrid Journal   (Followers: 5)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 23)
IEEE Solid-State Circuits Letters     Hybrid Journal   (Followers: 3)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 367)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 74)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 64)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 39)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 13)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 227)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 75)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 40)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 27)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 80)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 4)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 13)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 79)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 11)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 16)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 36)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 60)
IET Smart Grid     Open Access   (Followers: 1)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 12)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 12)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 38)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronic Science and Technology     Open Access   (Followers: 1)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 4)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 189)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 1)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
Journal of Power Electronics     Hybrid Journal   (Followers: 2)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 27)
Journal of Signal and Information Processing     Open Access   (Followers: 8)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 28)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 8)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 11)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 57)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Solid State Electronics Letters     Open Access  
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 2)

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APSIPA Transactions on Signal and Information Processing
Journal Prestige (SJR): 0.404
Citation Impact (citeScore): 2
Number of Followers: 9  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2048-7703 - ISSN (Online) 2048-7703
Published by Cambridge University Press Homepage  [387 journals]
  • Graph representation learning: a survey

    • Authors: Fenxiao Chen; Yun-Cheng Wang, Bin Wang, C.-C. Jay Kuo
      Abstract: Research on graph representation learning has received great attention in recent years since most data in real-world applications come in the form of graphs. High-dimensional graph data are often in irregular forms. They are more difficult to analyze than image/video/audio data defined on regular lattices. Various graph embedding techniques have been developed to convert the raw graph data into a low-dimensional vector representation while preserving the intrinsic graph properties. In this review, we first explain the graph embedding task and its challenges. Next, we review a wide range of graph embedding techniques with insights. Then, we evaluate several stat-of-the-art methods against small and large data sets and compare their performance. Finally, potential applications and future directions are presented.
      PubDate: 2020-05-28T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.13
      Issue No: Vol. 9 (2020)
  • High dynamic range image compression based on visual saliency

    • Authors: Jin Wang; Shenda Li, Qing Zhu
      Abstract: With wider luminance range than conventional low dynamic range (LDR) images, high dynamic range (HDR) images are more consistent with human visual system (HVS). Recently, JPEG committee releases a new HDR image compression standard JPEG XT. It decomposes an input HDR image into base layer and extension layer. The base layer code stream provides JPEG (ISO/IEC 10918) backward compatibility, while the extension layer code stream helps to reconstruct the original HDR image. However, this method does not make full use of HVS, causing waste of bits on imperceptible regions to human eyes. In this paper, a visual saliency-based HDR image compression scheme is proposed. The saliency map of tone mapped HDR image is first extracted, then it is used to guide the encoding of extension layer. The compression quality is adaptive to the saliency of the coding region of the image. Extensive experimental results show that our method outperforms JPEG XT profile A, B, C and other state-of-the-art methods. Moreover, our proposed method offers the JPEG compatibility at the same time.
      PubDate: 2020-05-27T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.15
      Issue No: Vol. 9 (2020)
  • Dimensional speech emotion recognition from speech features and word
           embeddings by using multitask learning

    • Authors: Bagus Tris Atmaja; Masato Akagi
      Abstract: The majority of research in speech emotion recognition (SER) is conducted to recognize emotion categories. Recognizing dimensional emotion attributes is also important, however, and it has several advantages over categorical emotion. For this research, we investigate dimensional SER using both speech features and word embeddings. The concatenation network joins acoustic networks and text networks from bimodal features. We demonstrate that those bimodal features, both are extracted from speech, improve the performance of dimensional SER over unimodal SER either using acoustic features or word embeddings. A significant improvement on the valence dimension is contributed by the addition of word embeddings to SER system, while arousal and dominance dimensions are also improved. We proposed a multitask learning (MTL) approach for the prediction of all emotional attributes. This MTL maximizes the concordance correlation between predicted emotion degrees and true emotion labels simultaneously. The findings suggest that the use of MTL with two parameters is better than other evaluated methods in representing the interrelation of emotional attributes. In unimodal results, speech features attain higher performance on arousal and dominance, while word embeddings are better for predicting valence. The overall evaluation uses the concordance correlation coefficient score of the three emotional attributes. We also discuss some differences between categorical and dimensional emotion results from psychological and engineering perspectives.
      PubDate: 2020-05-27T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.14
      Issue No: Vol. 9 (2020)
  • An analysis of speaker dependent models in replay detection

    • Authors: Gajan Suthokumar; Kaavya Sriskandaraja, Vidhyasaharan Sethu, Eliathamby Ambikairajah, Haizhou Li
      Abstract: Most research on replay detection has focused on developing a stand-alone countermeasure that runs independently of a speaker verification system by training a single spoofed model and a single genuine model for all speakers. In this paper, we explore the potential benefits of adapting the back-end of a spoofing detection system towards the claimed target speaker. Specifically, we characterize and quantify speaker variability by comparing speaker-dependent and speaker-independent (SI) models of feature distributions for both genuine and spoofed speech. Following this, we develop an approach for implementing speaker-dependent spoofing detection using a Gaussian mixture model (GMM) back-end, where both the genuine and spoofed models are adapted to the claimed speaker. Finally, we also develop and evaluate a speaker-specific neural network-based spoofing detection system in addition to the GMM based back-end. Evaluations of the proposed approaches on replay corpora BTAS2016 and ASVspoof2017 v2.0 reveal that the proposed speaker-dependent spoofing detection outperforms equivalent SI replay detection baselines on both datasets. Our experimental results show that the use of speaker-specific genuine models leads to a significant improvement (around 4% in terms of equal error rate (EER)) as previously shown and the addition of speaker-specific spoofed models adds a small improvement on top (less than 1% in terms of EER).
      PubDate: 2020-04-30T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.9
      Issue No: Vol. 9 (2020)
  • An overview of ongoing point cloud compression standardization activities:
           video-based (V-PCC) and geometry-based (G-PCC)

    • Authors: D. Graziosi; O. Nakagami, S. Kuma, A. Zaghetto, T. Suzuki, A. Tabatabai
      Abstract: This article presents an overview of the recent standardization activities for point cloud compression (PCC). A point cloud is a 3D data representation used in diverse applications associated with immersive media including virtual/augmented reality, immersive telepresence, autonomous driving and cultural heritage archival. The international standard body for media compression, also known as the Motion Picture Experts Group (MPEG), is planning to release in 2020 two PCC standard specifications: video-based PCC (V-CC) and geometry-based PCC (G-PCC). V-PCC and G-PCC will be part of the ISO/IEC 23090 series on the coded representation of immersive media content. In this paper, we provide a detailed description of both codec algorithms and their coding performances. Moreover, we will also discuss certain unique aspects of point cloud compression.
      PubDate: 2020-04-03T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.12
      Issue No: Vol. 9 (2020)
  • Color-gamut mapping in the non-uniform CIE-1931 space with perceptual hue
           fidelity constraints for SMPTE ST.2094-40 standard

    • Authors: Chang Su; Li Tao, Yeong Taeg Kim
      Abstract: As high-dynamic range (HDR) and wide-color gamut (WCG) contents become more and more popular in multimedia markets, color mapping of the distributed contents to different rendering devices plays a pivotal role in HDR distribution eco-systems. The widely used and economic gamut-clipping (GC)-based techniques perform poorly in mapping WCG contents to narrow gamut devices; and high-performance color-appearance model (CAM)-based techniques are computationally expensive to commercial applications. In this paper, we propose a novel color gamut mapping (CGM) algorithm to solve the problem. By introducing a color transition/protection zone (TPZ) and a set of perceptual hue fidelity constraints into the CIE-1931 space, the proposed algorithm directly carries out CGM in the perceptually non-uniform space, thus greatly decreases the computational complexity. The proposed TPZ effectively achieves a reasonable compromise between saturation preserving and details protection in out-of-gamut colors. The proposed hue fidelity constraints reference the measurements of human subjects' visual responses, thus effectively preserve the perceptual hue of the original colors. Experimental results show that the proposed algorithm clearly outperforms the GC-CGM, and performs similarly or better than the expensive CAM-CGM. The proposed algorithm is real-time and hardware friendly. It is an important supplement of the SMPTE ST.2094-40 standard.
      PubDate: 2020-03-31T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.11
      Issue No: Vol. 9 (2020)
  • Vision and language: from visual perception to content creation

    • Authors: Tao Mei; Wei Zhang, Ting Yao
      Abstract: Vision and language are two fundamental capabilities of human intelligence. Humans routinely perform tasks through the interactions between vision and language, supporting the uniquely human capacity to talk about what they see or hallucinate a picture on a natural-language description. The valid question of how language interacts with vision motivates us researchers to expand the horizons of computer vision area. In particular, “vision to language” is probably one of the most popular topics in the past 5 years, with a significant growth in both volume of publications and extensive applications, e.g. captioning, visual question answering, visual dialog, language navigation, etc. Such tasks boost visual perception with more comprehensive understanding and diverse linguistic representations. Going beyond the progresses made in “vision to language,” language can also contribute to vision understanding and offer new possibilities of visual content creation, i.e. “language to vision.” The process performs as a prism through which to create visual content conditioning on the language inputs. This paper reviews the recent advances along these two dimensions: “vision to language” and “language to vision.” More concretely, the former mainly focuses on the development of image/video captioning, as well as typical encoder–decoder structures and benchmarks, while the latter summarizes the technologies of visual content creation. The real-world deployment or services of vision and language are elaborated as well.
      PubDate: 2020-03-30T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.10
      Issue No: Vol. 9 (2020)
  • Multiple feature regularized kernel for hyperspectral imagery

    • Authors: Xu Yan; Peng Jiangtao, Du Qian
      Abstract: In this paper, a multiple feature regularized kernel is proposed for hyperspectral imagery classification. To exploit the label information, a regularized kernel is used to refine the original kernel in the Support Vector Machine classifier. Furthermore, since spatial features have been widely investigated for hyperspectral imagery classification, different types of spatial features including spectral feature, local feature (i.e. local binary pattern), global feature (i.e. Gabor feature), and shape feature (i.e. extended multiattribute profiles) are included to provide distinguish discriminative information. Finally, a majority voting-based ensemble approach, which combines different types of features, is adopted to further increase the classification performance. Combining different discriminative feature information can improve the classification performance since one type of feature may result in poor performance, especially when the number of training samples is limited. Experimental results demonstrated that the proposed approach has superior performance compared with the state-of-the-art classifiers.
      PubDate: 2020-03-26T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.8
      Issue No: Vol. 9 (2020)
  • Theoretical analysis of skip connections and batch normalization from
           generalization and optimization perspectives

    • Authors: Yasutaka Furusho; Kazushi Ikeda
      Abstract: Deep neural networks (DNNs) have the same structure as the neocognitron proposed in 1979 but have much better performance, which is because DNNs include many heuristic techniques such as pre-training, dropout, skip connections, batch normalization (BN), and stochastic depth. However, the reason why these techniques improve the performance is not fully understood. Recently, two tools for theoretical analyses have been proposed. One is to evaluate the generalization gap, defined as the difference between the expected loss and empirical loss, by calculating the algorithmic stability, and the other is to evaluate the convergence rate by calculating the eigenvalues of the Fisher information matrix of DNNs. This overview paper briefly introduces the tools and shows their usefulness by showing why the skip connections and BN improve the performance.
      PubDate: 2020-02-27T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.7
      Issue No: Vol. 9 (2020)
  • A two-stage approach for passive sound source localization based on the
           SRP-PHAT algorithm

    • Authors: M.A. Awad-Alla; Ahmed Hamdy, Farid A. Tolbah, Moatasem A. Shahin, M.A. Abdelaziz
      Abstract: This paper presents a different approach to tackle the Sound Source Localization (SSL) problem apply on a compact microphone array that can be mounted on top of a small moving robot in an indoor environment. Sound source localization approaches can be categorized into the three main categories; Time Difference of Arrival (TDOA), high-resolution subspace-based methods, and steered beamformer-based methods. Each method has its limitations according to the search or application requirements. Steered beamformer-based method will be used in this paper because it has proven to be robust to ambient noise and reverberation to a certain extent. The most successful and used algorithm of this method is the SRP-PHAT algorithm. The main limitation of SRP-PHAT algorithm is the computational burden resulting from the search process, this limitation comes from searching among all possible candidate locations in the searching space for the location that maximizes a certain function. The aim of this paper is to develop a computationally viable approach to find the coordinate location of a sound source with acceptable accuracy. The proposed approach comprises two stages: the first stage contracts the search space by estimating the Direction of Arrival (DoA) vector from the time difference of arrival with an addition of reasonable error coefficient around the vector to make sure that the sound source locates inside the estimated region, the second stage is to apply the SRP-PHAT algorithm to search only in this contracted region for the source location. The AV16.3 corpus was used to evaluate the proposed approach, extensive experiments have been carried out to verify the reliability of the approach. The results showed that the proposed approach was successful in obtaining good results compared to the conventional SRP-PHAT algorithm.
      PubDate: 2020-02-26T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.6
      Issue No: Vol. 9 (2020)
  • An Overview of Coding Tools in AV1: the First Video Codec from the
           Alliance for Open Media

    • Authors: Yue Chen; Debargha Mukherjee, Jingning Han, Adrian Grange, Yaowu Xu, Sarah Parker, Cheng Chen, Hui Su, Urvang Joshi, Ching-Han Chiang, Yunqing Wang, Paul Wilkins, Jim Bankoski, Luc Trudeau, Nathan Egge, Jean-Marc Valin, Thomas Davies, Steinar Midtskogen, Andrey Norkin, Peter de Rivaz, Zoe Liu
      Abstract: In 2018, the Alliance for Open Media (AOMedia) finalized its first video compression format AV1, which is jointly developed by the industry consortium of leading video technology companies. The main goal of AV1 is to provide an open source and royalty-free video coding format that substantially outperforms state-of-the-art codecs available on the market in compression efficiency while remaining practical decoding complexity as well as being optimized for hardware feasibility and scalability on modern devices. To give detailed insights into how the targeted performance and feasibility is realized, this paper provides a technical overview of key coding techniques in AV1. Besides, the coding performance gains are validated by video compression tests performed with the libaom AV1 encoder against the libvpx VP9 encoder. Preliminary comparison with two leading HEVC encoders, x265 and HM, and the reference software of VVC is also conducted on AOM's common test set and an open 4k set.
      PubDate: 2020-02-24T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.2
      Issue No: Vol. 9 (2020)
  • Fully-automatic inverse tone mapping algorithm based on dynamic mid-level
           tone mapping

    • Authors: Gonzalo Luzardo; Jan Aelterman, Hiep Luong, Sven Rousseaux, Daniel Ochoa, Wilfried Philips
      Abstract: High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state-of-the-art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques.
      PubDate: 2020-02-24T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.5
      Issue No: Vol. 9 (2020)
  • Video bit-rate requirements for 8K 120-Hz HEVC/H.265 temporal scalable
           coding: experimental study based on 8K subjective evaluations

    • Authors: Yasuko Sugito; Shinya Iwasaki, Kazuhiro Chida, Kazuhisa Iguchi, Kikufumi Kanda, Xuying Lei, Hidenobu Miyoshi, Kimihiko Kazui
      Abstract: 8K video parameters were designed to provide an immersive experience; meanwhile, special considerations are necessary to assess the entire screen subjectively. This paper studies the video bit-rate required for 8K 119.88-Hz (120-Hz) and 59.94-Hz (60-Hz) the high efficiency video coding (HEVC)/H.265 temporal scalable coding based on subjective evaluation experiments. To investigate the appropriate bit-rate for both 8K 120- and 60-Hz videos for broadcasting purposes, we compress 8K 120-Hz test sequences using software that emulates our real-time HEVC encoder and conduct two types of experiments. The experimental results demonstrate that the required video bit-rate for 8K 120-Hz temporal scalable coding is estimated to be 85–110 Mbps, which is equivalent to the practical bit-rate for 8K 60-Hz videos, and the appropriate bit-rate for 8K 60-Hz video in 8K 120-Hz video at 85 Mbps is assumed to be ~80 Mbps. From the analyses of the encoded videos, it is confirmed that the experimental results are primarily influenced by the image quality on the slice boundary positioned at the middle of the screen height. When conducting the experiments, we determined settings referring to an initial 8K subjective assessment; we further mention requirements for future 8K subjective evaluations from the experimental results.
      PubDate: 2020-02-03T00:00:00.000Z
      DOI: 10.1017/ATSIP.2020.4
      Issue No: Vol. 9 (2020)
  • Signal denoising using the minimum-probability-of-error criterion

    • Authors: Jishnu Sadasivan; Subhadip Mukherjee, Chandra Sekhar Seelamantula
      Abstract: We consider signal denoising via transform-domain shrinkage based on a novel risk criterion called the minimum probability of error (MPE), which measures the probability that the estimated parameter lies outside an ε-neighborhood of the true value. The underlying parameter is assumed to be deterministic. The MPE, similar to the mean-squared error (MSE), depends on the ground-truth parameter, and therefore, has to be estimated from the noisy observations. The optimum shrinkage parameter is obtained by minimizing an estimate of the MPE. When the probability of error is integrated over ε, it leads to the expected ℓ1 distortion. The proposed MPE and ℓ1 distortion formulations are applicable to various noise distributions by invoking a Gaussian mixture model approximation. Within the realm of MPE, we also develop a specific extension to subband shrinkage. The denoising performance of MPE turns out to be better than that obtained using the minimum MSE-based approaches formulated within Stein's unbiased risk estimation (SURE) framework, especially in the low signal-to-noise ratio (SNR) regime. Performance comparisons with three benchmarking algorithms carried out on electrocardiogram signals and standard test signals taken from the Wavelab toolbox show that the MPE framework results in SNR gains particularly for low input SNR.
      PubDate: 2020-01-20T00:00:00.000Z
      DOI: 10.1017/ATSIP.2019.27
      Issue No: Vol. 9 (2020)
  • Learning priors for adversarial autoencoders

    • Authors: Hui-Po Wang; Wen-Hsiao Peng, Wei-Jan Ko
      Abstract: Most deep latent factor models choose simple priors for simplicity, tractability, or not knowing what prior to use. Recent studies show that the choice of the prior may have a profound effect on the expressiveness of the model, especially when its generative network has limited capacity. In this paper, we propose to learn a proper prior from data for adversarial autoencoders (AAEs). We introduce the notion of code generators to transform manually selected simple priors into ones that can better characterize the data distribution. Experimental results show that the proposed model can generate better image quality and learn better disentangled representations than AAEs in both supervised and unsupervised settings. Lastly, we present its ability to do cross-domain translation in a text-to-image synthesis task.
      PubDate: 2020-01-20T00:00:00.000Z
      DOI: 10.1017/ATSIP.2019.25
      Issue No: Vol. 9 (2020)
  • Advances in anti-spoofing: from the perspective of ASVspoof challenges

    • Authors: Madhu R. Kamble; Hardik B. Sailor, Hemant A. Patil, Haizhou Li
      Abstract: In recent years, automatic speaker verification (ASV) is used extensively for voice biometrics. This leads to an increased interest to secure these voice biometric systems for real-world applications. The ASV systems are vulnerable to various kinds of spoofing attacks, namely, synthetic speech (SS), voice conversion (VC), replay, twins, and impersonation. This paper provides the literature review of ASV spoof detection, novel acoustic feature representations, deep learning, end-to-end systems, etc. Furthermore, the paper also summaries previous studies of spoofing attacks with emphasis on SS, VC, and replay along with recent efforts to develop countermeasures for spoof speech detection (SSD) task. The limitations and challenges of SSD task are also presented. While several countermeasures were reported in the literature, they are mostly validated on a particular database, furthermore, their performance is far from perfect. The security of voice biometrics systems against spoofing attacks remains a challenging topic. This paper is based on a tutorial presented at APSIPA Annual Summit and Conference 2017 to serve as a quick start for those interested in the topic.
      PubDate: 2020-01-15T00:00:00.000Z
      DOI: 10.1017/ATSIP.2019.21
      Issue No: Vol. 9 (2020)
  • Toward human-centric deep video understanding

    • Authors: Wenjun Zeng
      Abstract: People are the very heart of our daily work and life. As we strive to leverage artificial intelligence to empower every person on the planet to achieve more, we need to understand people far better than we can today. Human–computer interaction plays a significant role in human-machine hybrid intelligence, and human understanding becomes a critical step in addressing the tremendous challenges of video understanding. In this paper, we share our views on why and how to use a human centric approach to address the challenging video understanding problems. We discuss human-centric vision tasks and their status, highlighting the challenges and how our understanding of human brain functions can be leveraged to effectively address some of the challenges. We show that semantic models, view-invariant models, and spatial-temporal visual attention mechanisms are important building blocks. We also discuss the future perspectives of video understanding.
      PubDate: 2020-01-01T00:00:00.000Z
      DOI: 10.1017/atsip.2019.26
      Issue No: Vol. 9 (2020)
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