检索结果-内蒙古大学图书馆

IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1816-1830页

作者： Xiao, Hongli Wang, Bingshu Zheng, Jiangbin Liu, Licheng Philip Chen, C.L. Northwestern Polytechnical University School of Software Taicang Campus Suzhou215400 China Shanghai Jiaotong University School of Electronic Information and Electrical Engineering Shanghai200240 China Hunan University College of Electrical and Information Engineering Changsha410082 China South China University of Technology School of Computer Science and Engineering Guangzhou510641 China

The fast outbreak of coronavirus disease 2019 (COVID-19) and rapid proliferation of its variants have continued to pose a huge challenge to people around the world. Wearing medical masks properly in public and private settings can protect people from COVID-19, which brings a growing demand for automatic detection services of face mask wearing conditions. In this article, we propose a fine-grained detector called ECA_YOLOX-S to identify the wearing status of face masks. Efficient channel attention is introduced into YOLOX-S to reach a tradeoff between effectiveness and efficiency. To demonstrate the performance of our proposed method, a Fine-grained Face Mask (FineFM) dataset is created, which covers four classes of mask wearing status. The proposed FineFM dataset has 16 955 annotated images and covers multiple realistic scenarios. To the best of authors' knowledge, it has the largest number of improper mask wearing images among all similar datasets for realistic scenes. Experiments conducted on the FineFM dataset demonstrate that ECA_YOLOX-S achieves an overall mean average precision (mAP)@.50:95 of 86.80% for moderate scenes and an overall mAP@.50:95 of 73.20% for complex scenes, outperforming its benchmark model. Moreover, experiments conducted on other realistic and simulated datasets indicate that the proposed detector has advantages over other methods. © 2020 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Active pixel image sensor array for dual vision using large-area bilayer WS_(2)

引用

InfoMat 2024年第4期6卷 68-82页

作者： Arindam Bala Mayuri Sritharan Na Liu Muhammad Naqi Anamika Sen Gyuchull Han Hyun Yeol Rho Youngki Yoon Sunkook Kim School of Advanced Materials Science and Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Waterloo Institute for Nanotechnology(WIN) University of WaterlooWaterlooOntarioCanada Department of Electrical and Computer Engineering University of WaterlooWaterlooOntarioCanada

Transition metal dichalcogenides(TMDs)are a promising candidate for developing advanced sensors,particularly for day and night vision systems in vehicles,drones,and security *** traditional systems rely on separate sensors for different lighting conditions,TMDs can absorb light across a broad-spectrum *** this study,a dual vision active pixel image sensor array based on bilayer WS2 phototransistors was *** bilayer WS2 film was synthesized using a combined process of radio-frequency sputtering and chemical vapor *** WS2-based thin-film transistors(TFTs)exhibit high average mobility,excellent Ion/Ioff,and uniform electrical *** optoelectronic properties of the TFTs array exhibited consistent behavior and can detect visible to near-infrared light with the highest responsivity of 1821 A W1(at a wavelength of 405 nm)owing to the photogating ***,red,green,blue,and near-infrared image sensing capabilities of active pixel image sensor array utilizing light stencil projection were *** proposed image sensor array utilizing WS2 phototransistors has the potential to revolutionize the field of vision sensing,which could lead to a range of new opportunities in various applications,including night vision,pedestrian detection,various surveillance,and security systems.

关键词： dual vision image sensors infrared wavelength detection phototransistors thin-film transistor arrays transition metal dichalcogenides

来源：评论

学校读者我要写书评

暂无评论

An efficient cloud based face recognition system for e-health secured login using steerable pyramid transform and local directional pattern

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 1017-1027页

作者： Dosaj, Ayush Satapathy, Suresh Chandra Soundrapandiyan, Rajkumar Kaur, Mannat Hannoon, Naeem School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Computer Science and Engineering Kalinga Institute of Industrial Technology Deemed to be University Odisha Bhubaneswar India Faculty of Electrical Engineering Universiti Teknologi MARA Shah Alam Malaysia

This paper proposes a face recognition system based on steerable pyramid transform (SPT) and local directional pattern (LDP) for e-health secured login in cloud domain. In an e-health login, patients periodically forget their self-made login username and password. This face recognition system can replace the traditional login system. In the proposed system, SPT can decompose a face image into several sub-bands of different scales and orientations, and LDP can encode the sub-bands in binary texture pattern. The LDP binary pattern was obtained by computing the edge response values in all eight directions at each pixel position and generating a code from the relative strength magnitude. Therefore, SPT–LDP design represents a face image in a robust way which includes multiple information sources from different scales and orientations. The proposed system is tested on standard benchmark facial recognition technology (FERET) and extended Yale-B databases. Further, the efficiency of the proposed system is proved by comparing recognition rates with other existing descriptor based methods. From the experimental results it is observed that the proposed system achieves 99.79% recognition in fb set, 90.72% in fc set, 84.97% in dup I set, and 87.69% in dup II set for FERET database and 100% in sub2 set, 100% in sub3 set, 96% in sub4 set and 95% in sub5 set for extended Yale-B database which is better than the existing methods. © Springer-Verlag GmbH Germany, part of Springer Nature 2018.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

A systematic literature review of visual feature learning: deep learning techniques, applications, challenges and future directions

引用

Multimedia Tools and Applications 2024年 1-58页

作者： Abdullahi, Mohammed Oyelade, Olaide Nathaniel Kana, Armand Florentin Donfack Bagiwa, Mustapha Aminu Abdullahi, Fatimah Binta Junaidu, Sahalu Balarabe Iliyasu, Ibrahim Ore-ofe, Ajayi Chiroma, Haruna Department of Computer Science Ahmadu Bello University Zaria Zaria Nigeria Department of Mechanical Engineering Ahmadu Bello University Zaria Nigeria Department of Computer Engineering Ahmadu Bello University Zaria Nigeria College of Computer Science and Engineering University of Hafr Al Batin Hafar Al-Batin31991 Saudi Arabia School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast United Kingdom

Visual Feature Learning (VFL) is a critical area of research in computer vision that involves the automatic extraction of features and patterns from images and videos. The applications of VFL are vast, including object detection and recognition, facial recognition, scene understanding, medical image analysis, and autonomous vehicles. In this paper, we propose to conduct extensive systematic literature review (SLR) on VFL based on deep learning algorithms. The paper conducted an SLR covering deep learning algorithms such as Convolutional Neural Networks (CNNs), Autoencoders, and Generative Adversarial Networks (GANs) including their variants. The review highlights the importance of VFL in computer vision and the limitations of traditional feature extraction techniques. Furthermore, it provides an in-depth analysis of the strengths and weaknesses of various deep learning algorithms for solving problems in VFL. The discussion of the applications of VFL provides an insight into the impact of VFL on various industries and domains. The review also analyzed the challenges faced by VFL, such as data scarcity and quality, overfitting, generalization, interpretability, and explainability. The discussion of future directions for VFL includes hybrid techniques, unsupervised feature learning, continual learning, attention-based models, and explainable AI. These techniques aim to address the challenges faced by VFL and improve the performance of the models. The systematic literature review concludes that VFL is a rapidly evolving field with the potential to transform many industries and domains. The review highlights the need for further research in VFL and emphasizes the importance of responsible use of VFL models in various applications. The review provides valuable insights for researchers and practitioners in the field of computer vision, who can use these insights to enhance their work and ensure the responsible use of VFL models. © The Author(s), under exclusive licence to

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

FPMT: Enhanced Semi-supervised Model for Traffic Incident Detection 27th

FPMT: Enhanced Semi-supervised Model for Traffic Incident De...

引用

27th international Conference on Pattern Recognition, ICPR 2024

作者： Lu, Xinying Xiao, Jianli School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9783031781063

For traffic incident detection, the acquisition of data and labels is notably resource-intensive, rendering semi-supervised traffic incident detection both a formidable and consequential challenge. Thus, this paper focuses on traffic incident detection with a semi-supervised learning way. It proposes a semi-supervised learning model named FPMT within the framework of MixText. The data augmentation module introduces Generative Adversarial Networks to balance and expand the dataset. During the mix-up process in the hidden space, it employs a probabilistic pseudo-mixing mechanism to enhance regularization and elevate model precision. In terms of training strategy, it initiates with unsupervised training on all data, followed by supervised fine-tuning on a subset of labeled data, and ultimately completing the goal of semi-supervised training. Through empirical validation on four authentic datasets, our FPMT model exhibits outstanding performance across various metrics. Particularly noteworthy is its robust performance even in scenarios with low label rates. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Data Quality-Driven Top-k Rule Discovery 3rd

Data Quality-Driven Top-k Rule Discovery

引用

3rd international Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Han, Ziyan Chen, Wanjia Han, Yunpeng School of Computer Science and Engineering Beihang University Beijing China School of Mathematical Sciences Shenzhen University Shenzhen China School of Electrical Engineering and Computer Science Louisiana State University Baton Rouge United States

ISBN: (纸本)9789819616978

Existing works on rule discovery often yield an overwhelming number of rules with a high computational cost. Moreover, few studies consider the impact of data quality on the reliability of rules produced. This paper studies the top-k rule discovery problem that returns a set of top-k reliable rules. We introduce a novel scoring function that incorporates data quality, providing a more comprehensive and fine-grained assessment of rules. Based on this scoring function, we develop an efficient algorithm for discovering top-k high-quality rules in relational data. To enhance the performance of our algorithm, we propose effective pruning and optimization strategies that significantly reduce the search space and improve computational efficiency;additionally, we parallelize it for further acceleration. Through extensive experiments on real-life datasets, we verify the effectiveness and efficiency of the proposed method, confirming its practical utility in data quality-driven top-k rule discovery. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data reliability

来源：评论

学校读者我要写书评

暂无评论

Towards Explainable Network Intrusion Detection using Large Language Models 11

Towards Explainable Network Intrusion Detection using Large ...

引用

11th IEEE/ACM international Conference on Big Data Computing, Applications and Technologies, BDCAT 2024

作者： Houssel, Paul R. B. Singh, Priyanka Layeghy, Siamak Portmann, Marius The University of Queensland School of Computer Science and Electrical Engineering BrisbaneQLD 4072 Australia

ISBN: (纸本)9798350367300

Large Language Models (LLMs) have revolutionised natural language processing tasks, particularly as chat agents. However, their applicability to threat detection problems remains unclear. This paper examines the feasibility of employing LLMs as a Network Intrusion Detection System (NIDS), despite their high computational requirements, primarily for the sake of explain-ability. Furthermore, considerable resources have been invested in developing LLMs, and they may offer utility for NIDS. Current state-of-the-art NIDS rely on artificial benchmarking datasets, resulting in skewed performance when applied to real-world networking environments. Therefore, we compare the GPT-4 and LLama3 models against traditional architectures and transformer-based models to assess their ability to detect malicious NetFlows without depending on artificially skewed datasets, but solely on their vast pre-trained acquired knowledge. Our results reveal that, although LLMs struggle with precise attack detection, they hold significant potential for a path towards explainable NIDS. Our preliminary exploration shows that LLMs are unfit for the detection of Malicious NetFlows. Most promisingly, however, these exhibit significant potential as complementary agents in NIDS, particularly in providing explanations and aiding in threat response when integrated with Retrieval Augmented Generation (RAG) and function calling capabilities. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Bi-level Optimal Operation Model of Mobile Energy Storage System in Coupled Transportation-power Networks

引用

Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1725-1737页

作者： Weiqing Sun Wei Liu Jie Zhang Kunpeng Tian School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

The operation characteristics of energy storage can help the distribution network absorb more renewable energy while improving the safety and economy of the power *** energy storage systems(MESSs)have a broad application market compared with stationary energy storage systems and electric vehicles due to their flexible mobility and good dispatch ***,when urban traffic flows rise,the congested traffic environment will prolong the transit time of MESS,which will ultimately affect the operation state of the power networks and the economic benefits of *** paper proposes a bi-level optimization model for the economic operation of MESS in coupled transportation-power networks,considering road congestion and the operation constraints of the power *** upper-level model depicts the daily operation scheme of MESS devised by the distribution network operator(DNO)in order to maximize the total revenue of the *** fuzzy time windows and fuzzy road congestion indexes,the lower-level model optimizes the route for the transit problem of ***,road congestion that affects the transit time of MESS can be fully incorporated in the optimal operation *** the IEEE 33-bus distribution network and the 29-node transportation network are used to verify and examine the effectiveness of the proposed *** simulation results demonstrate that the operation scheme of MESS will avoid the congestion period when considering road ***,the transit energy consumption and the impact of the traffic environment on the economic benefits of MESS can be reduced.

关键词： Mobile energy storage system economic dispatch bi-level optimization model road congestion fuzzy constraint

来源：评论

学校读者我要写书评

暂无评论

Towards a Low-Cost Distributed AWOS: Machine Learning for Optical Ceilometry

Towards a Low-Cost Distributed AWOS: Machine Learning for Op...

引用

AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Dhakal, Rabin Mourning, Chad School of Electrical Engineering and Computer Science Ohio University AthensOH45701 United States

ISBN: (纸本)9781624107238

Automated Surface/Weather Observing Systems (ASOS/AWOS) are the surface weather observation stations located throughout the United States. This weather station relies upon sensing instruments that disseminate the weather data and broadcast it over the radio or the ground link in METAR Format. ASOS station accumulates complex weather data and is useful for weather forecasting or climatology applications. On the other hand, AWOS focuses on aviation-specific weather data, catering primarily to the needs of pilots and airport operations. Weather data is comprised of visibility, wind speed, cloud coverage information, temperature and humidity, etc. AWOS depends upon the ceilometer for estimating the cloud coverage and its location from the ground. Accurately estimating cloud-base height typically requires a costly ceilometer system, which uses advanced instrumentation to measure cloud height precisely. This research addresses this challenge by proposing a cost-effective alternative that uses optical cameras, offering a more affordable solution without compromising functionality. Implementing computer vision and synthetic data in a virtual environment, our proposed method achieves an RMSE of 193.91 meters on 442 previously unseen synthetic test samples, demonstrating its potential as a reliable and efficient alternative. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Wind

来源：评论

学校读者我要写书评

暂无评论

New Delay Doppler Communication Paradigm in 6G Era:A Survey of Orthogonal Time Frequency Space(OTFS)

引用

China Communications 2023年第6期20卷 1-25页

作者： Weijie Yuan Shuangyang Li Zhiqiang Wei Yuanhao Cui Jiamo Jiang Haijun Zhang Pingzhi Fan Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhenChina Faculty of Electrical Engineering and Computer Science Technical University of BerlinBerlinGermany School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’anChina Department of Communication Engineering Beijing University of Posts and TelecommunicationsBeijingChina China Academy of Information and Communications Technology BeijingChina School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina School of Information Science and Technology Southwest Jiaotong UniversityChengduChina

In the 6G era,Space-Air-Ground Integrated Network(SAGIN)are anticipated to deliver global coverage,necessitating support for a diverse array of emerging applications in high-mobility,hostile *** such conditions,conventional orthogonal frequency division multiplexing(OFDM)modulation,widely employed in cellular and Wi-Fi communication systems,experiences performance degradation due to significant Doppler *** overcome this obstacle,a novel twodimensional(2D)modulation approach,namely orthogonal time frequency space(OTFS),has emerged as a key enabler for future high-mobility use ***,OTFS modulates information within the delay-Doppler(DD)domain,as opposed to the timefrequency(TF)domain utilized by *** offers advantages such as Doppler and delay resilience,reduced signaling latency,a lower peak-to-average ratio(PAPR),and a reduced-complexity *** studies further indicate that the direct interplay between information and the physical world in the DD domain positions OTFS as a promising waveform for achieving integrated sensing and communications(ISAC).In this article,we present an in-depth review of OTFS technology in the context of the 6G era,encompassing fundamentals,recent advancements,and future *** objective is to provide a helpful resource for researchers engaged in the field of OTFS.

关键词： OTFS 6G delay-Doppler(DD)domain

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：