IEEE Journal on Emerging and Selected Topics in Circuits and Systems最新文献_第2页

Energy-Efficient Saliency-Guided Video Coding Framework for Real-Time Applications 面向实时应用的高能效显著性视频编码框架

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2025-01-02 DOI: 10.1109/JETCAS.2024.3525339

Tero Partanen;Minh Hoang;Alexandre Mercat;Joose Sainio;Jarno Vanne

{"title":"Energy-Efficient Saliency-Guided Video Coding Framework for Real-Time Applications","authors":"Tero Partanen;Minh Hoang;Alexandre Mercat;Joose Sainio;Jarno Vanne","doi":"10.1109/JETCAS.2024.3525339","DOIUrl":"https://doi.org/10.1109/JETCAS.2024.3525339","url":null,"abstract":"The significant growth in global video data traffic can be mitigated by saliency-based video coding schemes that seek to increase coding efficiency without any loss of objective visual quality by compressing salient video regions less heavily than non-salient regions. However, conducting salient object detection (SOD) on every video frame before encoding tends to lead to substantial complexity and energy consumption overhead, especially if state-of-the-art deep learning techniques are used in saliency detection. This work introduces a saliency-guided video encoding framework that reduces the energy consumption over frame-by-frame SOD by increasing the detection interval and applying the proposed region-of-interest (ROI) tracking between successive detections. The computational complexity of our ROI tracking technique is kept low by predicting object movements from motion vectors, which are inherently calculated during encoding. Our experimental results demonstrate that the proposed ROI tracking solution saves energy by 86-95% and attains 84-94% accuracy over frame-by-frame SOD. Correspondingly, integrating our proposal into the complete saliency-guided video coding scheme reduces energy consumption on CPU by 79-82% at a cost of weighted PSNR of less than 5%. These findings indicate that our solution has significant potential for low-cost and low-power streaming media applications.","PeriodicalId":48827,"journal":{"name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","volume":"15 1","pages":"44-57"},"PeriodicalIF":3.7,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820524","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Compact Visual Data Representation for Green Multimedia–A Human Visual System Perspective 绿色多媒体的紧凑视觉数据表示——人类视觉系统视角

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-30 DOI: 10.1109/JETCAS.2024.3524260

Peilin Chen;Xiaohan Fang;Meng Wang;Shiqi Wang;Siwei Ma

引用次数: 0

Low-Power Multiversion Interpolation Filter Accelerator With Hardware Reuse for AV1 Codec 低功耗多版本插值滤波器加速器与硬件复用AV1编解码器

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-25 DOI: 10.1109/JETCAS.2024.3523246

Daiane Freitas;Patrick Rosa;Leonardo Müller;Daniel Palomino;Cláudio M. Diniz;Mateus Grellert;Guilherme Corrêa

{"title":"Low-Power Multiversion Interpolation Filter Accelerator With Hardware Reuse for AV1 Codec","authors":"Daiane Freitas;Patrick Rosa;Leonardo Müller;Daniel Palomino;Cláudio M. Diniz;Mateus Grellert;Guilherme Corrêa","doi":"10.1109/JETCAS.2024.3523246","DOIUrl":"https://doi.org/10.1109/JETCAS.2024.3523246","url":null,"abstract":"In modern video encoders, sub-pixel motion models are used to represent smoother transitions between neighboring frames, which is specially useful in regions with intense movement. The AV1 video codec introduces adaptive filtering for sub-pixel interpolation in the inter-frame prediction stage, enhancing flexibility in Motion Estimation (ME) and Motion Compensation (MC), using three filter types: Regular, Sharp, and Smooth. However, the increased variety of filters leads to higher complexity and energy consumption, particularly during the resource-intensive generation of sub-pixel samples. To address this challenge, this paper presents a hardware accelerator optimized for AV1 interpolation, incorporating energy-saving features for unused filters. The accelerator includes one precise version that can be used for both MC and ME and two approximate versions for ME, designed to maximize hardware efficiency and minimize implementation costs. The proposed design can process videos at resolutions up to 4320p at 50 frames per second for MC and 2,656.14 million samples per second for ME, with a power dissipation ranging between 21.25 mW and 40.06 mW, and an average coding efficiency loss of 0.67% and 1.11%, depending on the filter type and version.","PeriodicalId":48827,"journal":{"name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","volume":"15 1","pages":"133-142"},"PeriodicalIF":3.7,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Information for Authors IEEE关于电路和系统信息中新兴和选定主题的作者期刊

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-13 DOI: 10.1109/JETCAS.2024.3502893

引用次数: 0

Erratum to “A Reconfigurable Spatial Architecture for Energy-Efficient Inception Neural Networks” “可重构的节能初始神经网络空间结构”的勘误

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-13 DOI: 10.1109/JETCAS.2024.3464190

Lichuan Luo;Wang Kang;Junzhan Liu;He Zhang;Youguang Zhang;Dijun Liu;Peng Ouyang

引用次数: 0

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Publication Information 电气和电子工程师学会电路与系统新专题与选题期刊》出版信息

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-13 DOI: 10.1109/JETCAS.2024.3502897

引用次数: 0

IEEE Circuits and Systems Society Information 电气和电子工程师学会电路与系统协会信息

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-13 DOI: 10.1109/JETCAS.2024.3502895

引用次数: 0

Guest Editorial: Toward Trustworthy AI: Advances in Circuits, Systems, and Applications 客座编辑：迈向可信赖的人工智能：电路、系统和应用的进展

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-13 DOI: 10.1109/JETCAS.2024.3497232

Shih-Hsu Huang;Pin-Yu Chen;Stjepan Picek;Chip-Hong Chang

引用次数: 0

LSHIM: Low-Power and Small-Area Inexact Multiplier for High-Speed Error-Resilient Applications LSHIM：用于高速容错应用的低功耗小面积不精确乘法器

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-12-11 DOI: 10.1109/JETCAS.2024.3515055

Azin Izadi;Vahid Jamshidi

{"title":"LSHIM: Low-Power and Small-Area Inexact Multiplier for High-Speed Error-Resilient Applications","authors":"Azin Izadi;Vahid Jamshidi","doi":"10.1109/JETCAS.2024.3515055","DOIUrl":"https://doi.org/10.1109/JETCAS.2024.3515055","url":null,"abstract":"Numerical computations in various applications can often tolerate a small degree of error. In fields such as data mining, encoding algorithms, image processing, machine learning, and signal processing where error resilience is crucial approximate computing can effectively replace precise computing to minimize circuit delay and power consumption. In these contexts, a certain level of error is permissible. Multiplication, a fundamental arithmetic operation in computer systems, often leads to increased circuit delay, power usage, and area occupation when performed accurately by multipliers, which are key components in these applications. Thus, developing an optimal multiplier represents a significant advantage for inexact computing systems. In this paper, we introduce a novel approximate multiplier based on the Mitchell algorithm. The proposed design has been implemented using the Cadence software environment with the TSMC 45nm standard-cell library and a supply voltage of 1.1V. Simulation results demonstrate an average reduction of 31.7% in area, 46.8% in power consumption, and 36.1% in circuit delay compared to previous works. The mean relative error distance (MRED) for the proposed method is recorded at 2.6%.","PeriodicalId":48827,"journal":{"name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","volume":"15 1","pages":"94-104"},"PeriodicalIF":3.7,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decision Guided Robust DL Classification of Adversarial Images Combining Weaker Defenses 决策引导下结合弱防御的对抗图像鲁棒深度学习分类

IF 3.7 2区工程技术

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-11-13 DOI: 10.1109/JETCAS.2024.3497295

Shubhajit Datta;Manaar Alam;Arijit Mondal;Debdeep Mukhopadhyay;Partha Pratim Chakrabarti

{"title":"Decision Guided Robust DL Classification of Adversarial Images Combining Weaker Defenses","authors":"Shubhajit Datta;Manaar Alam;Arijit Mondal;Debdeep Mukhopadhyay;Partha Pratim Chakrabarti","doi":"10.1109/JETCAS.2024.3497295","DOIUrl":"https://doi.org/10.1109/JETCAS.2024.3497295","url":null,"abstract":"Adversarial examples make Deep Learning (DL) models vulnerable to safe deployment in practical systems. Although several techniques have been proposed in the literature, defending against adversarial attacks is still challenging. The current work identifies weaknesses of traditional strategies in detecting and classifying adversarial examples. To overcome these limitations, we carefully analyze techniques like binary detector and ensemble method, and compose them in a manner which mitigates the limitations. We also effectively develop a re-attack strategy, a randomization technique called RRP (Random Resizing and Patch-removing), and a rule-based decision method. Our proposed method, BEARR (Binary detector with Ensemble and re-Attacking scheme including Randomization and Rule-based decision technique) detects adversarial examples as well as classifies those examples with a higher accuracy compared to contemporary methods. We evaluate BEARR on standard image classification datasets: CIFAR-10, CIFAR-100, and tiny-imagenet as well as two real-world datasets: plantvillage and chest X-ray in the presence of state-of-the-art adversarial attack techniques. We have also validated BEARR against a more potent attacker who has perfect knowledge of the protection mechanism. We observe that BEARR is significantly better than existing methods in the context of detection and classification accuracy of adversarial examples.","PeriodicalId":48827,"journal":{"name":"IEEE Journal on Emerging and Selected Topics in Circuits and Systems","volume":"14 4","pages":"758-772"},"PeriodicalIF":3.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0