Electronics Letters最新文献_第9页

High importance feature selection and DV-OSR-QSED strategy for open-set recognition

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-02-05 DOI: 10.1049/ell2.70167

Tong Xu

引用次数: 0

Multiple kernel-enhanced encoder for effective herbarium image segmentation

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-02-04 DOI: 10.1049/ell2.70155

Sanghyuck Lee, Hyeonji Moon, Sangtae Kim, Jaesung Lee

引用次数: 0

Deep circadian-informed probability refinement network for pedestrian intent classification in urban complex

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-31 DOI: 10.1049/ell2.70159

Ho Chun Wu, Paul Yuen, Esther Hoi Shan Lau, Kevin Hung, Kwok Tai Chui, Andrew Kwok Fai Lui

{"title":"Deep circadian-informed probability refinement network for pedestrian intent classification in urban complex","authors":"Ho Chun Wu, Paul Yuen, Esther Hoi Shan Lau, Kevin Hung, Kwok Tai Chui, Andrew Kwok Fai Lui","doi":"10.1049/ell2.70159","DOIUrl":"https://doi.org/10.1049/ell2.70159","url":null,"abstract":"Urban complexes often feature a mix of commercial, entertainment and recreational space serving a wide range of services. Pedestrian intent classification is hence crucial to identify their different destinations and understanding their needs. Moreover, circadian effects generally influence pedestrian behaviour. This paper proposes a deep circadian-informed probability refinement network for pedestrian intent classification (CIPRNet). It incorporates circadian information using a multiplexer network architecture to refine preliminary classification probabilities generated by a preliminary deep learning-based trajectory classifier. A joint loss function is used to co-optimize both the preliminary baseline trajectory classifier and the CIPRNet. Experimental results using real pedestrian trajectories captured from 3D range sensors at the Osaka Asia and Pacific Trade Centre (ATC) on a sunny day and cloudy day show that the CIPRNet can improve the state-of-the-art prediction of pedestrian paths by long short term memory classifier and trajectory unified transformer by approximately 13% and 10%, respectively. The CIPRNet is also extended to trajectory prediction and it outperformed various state-of-the-art algorithms in terms of average and final displacement error reduction. It may serve as an attractive alternative for pedestrian intent classification for urban complexes.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70159","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Insulated gate unipolar diode

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-31 DOI: 10.1049/ell2.70154

Iraj Sheikhian

引用次数: 0

An ISAR target motion estimation algorithm based on a differential semblance criterion

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-31 DOI: 10.1049/ell2.70147

D. P. Huxley, F. M. Watson, W. R. B. Lionheart

{"title":"An ISAR target motion estimation algorithm based on a differential semblance criterion","authors":"D. P. Huxley, F. M. Watson, W. R. B. Lionheart","doi":"10.1049/ell2.70147","DOIUrl":"https://doi.org/10.1049/ell2.70147","url":null,"abstract":"Inverse Synthetic Aperture Radar (ISAR) is a vital radar imaging technique that leverages the relative motion between the radar and the target to generate high-resolution images. Traditional ISAR methods; however, are highly sensitive to inaccuracies in estimating rotational parameters, roll, pitch, and yaw, leading to image degradation. This article proposes a novel Differential Semblance Optimization (DSO) criterion for imaging dynamically rotating targets in a multistatic ISAR configuration. Unlike the Intensity Criterion (IC), which requires a precise initial parameter range, DSO enables broader exploration of value ranges, offering greater flexibility. Although the experiments focus on yaw rotation, the method is versatile and extendable to other rotational parameters. Tests with varying transmitter and receiver configurations demonstrate that DSO maintains robust performance even with fewer receivers. Comparisons with IC show that DSO produces sharper, more focused images and performs robustly in noisy environments, underscoring its potential for enhancing ISAR imaging in complex and dynamic scenarios.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70147","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Multi-semantic contrast enhancement for robust insulator defect detection

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-31 DOI: 10.1049/ell2.70150

Yue Zhang, Zhiqiang Lin, Kunfeng Wei, Yonghui Xu, Lizhen Cui

{"title":"Multi-semantic contrast enhancement for robust insulator defect detection","authors":"Yue Zhang, Zhiqiang Lin, Kunfeng Wei, Yonghui Xu, Lizhen Cui","doi":"10.1049/ell2.70150","DOIUrl":"https://doi.org/10.1049/ell2.70150","url":null,"abstract":"The effectiveness of deep learning-based methods for insulator defect detection has been proven. However, in practical applications of power transmission lines, the complex and variable backgrounds in insulator images, coupled with the difficulty in labeling insulator defects, pose challenges to improving the robustness of such methods. Existing studies often utilize generative adversarial networks or forcefully combine foreground and background to augment training samples, but they overlook the rich semantic information in complex scenes, leading to distorted generated adversarial samples. To address this challenge, an innovative multi-semantic contrast enhancement method that significantly enhances the robustness of defect detection by deeply integrating high-level semantic knowledge and low-level signal priors is proposed. Moreover, through adversarial training using generated samples with diverse semantics and real samples, the robustness of the method is further improved. Experimental results demonstrate that this method surpasses state-of-the-art models, achieving significant performance on three independent cross-scene datasets.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70150","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

DarwinSync: An adaptive time step execution framework for large-scale neuromorphic systems

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-30 DOI: 10.1049/ell2.70153

Xiaofei Jin, Zonghua Gu, Yitao Li, Ziyang Kang, Youneng Hu, Huajin Tang, Gang Pan, De Ma

{"title":"DarwinSync: An adaptive time step execution framework for large-scale neuromorphic systems","authors":"Xiaofei Jin, Zonghua Gu, Yitao Li, Ziyang Kang, Youneng Hu, Huajin Tang, Gang Pan, De Ma","doi":"10.1049/ell2.70153","DOIUrl":"https://doi.org/10.1049/ell2.70153","url":null,"abstract":"The time step functions as a crucial temporal unit for simulating neuronal dynamics within spiking neural networks, which play a significant role in neuromorphic computing systems. Efficient management of these time steps is vital to ensure model accuracy while optimizing overall system performance. As system scale increases, variations in hardware across subsystems and their asynchronous operations create challenges in achieving effective time step control. To address this issue, this paper proposes an innovative framework for managing time steps in large-scale neuromorphic systems. This framework allows subsystems to dynamically adjust their time step lengths according to computational loads and to perform look-ahead computations. Such a strategy effectively reduces the overhead related to time step synchronization, enhancing system efficiency. Additionally, the paper introduces a safeguard mechanism to ensure the system's reliability. Experimental results indicate that the proposed framework sustains the correct long-term operation of the system and improves model execution performance by 8.88% to 27.15% when compared to existing methods.","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70153","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

A 6-b 875-MS/s SAR ADC with charge-pump based pipelined background metastability calibration

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-29 DOI: 10.1049/ell2.70148

Yunkuk Park, Se-Ung Park, Jung-Hoon Chun

引用次数: 0

Extended target tracking using neural network and Gaussian process

IF 0.7 4区工程技术

Electronics Letters Pub Date : 2025-01-26 DOI: 10.1049/ell2.70151

Hao Wang, Liping Song

引用次数: 0

A two-stage approach for single thermal image restoration