检索结果-内蒙古大学图书馆

2nd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis, FME 2022

作者： Liong, Gen-Bing See, John Liong, Sze-Teng Chan, Chee-Seng Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia School of Mathematical and Computing Sciences Heriot-Watt University Malaysia Putrajaya Malaysia Department of Electronic Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9781450394956

This paper considers the challenge of spotting facial macro- and micro-expression from long *** propose the multi-temporal stream network (MTSN) model that takes two distinct inputs by considering the different temporal information in the facial movement. We also introduce a hard and soft pseudo-labeling technique to enable the network to distinguish expression frames from nonexpression frames via the learning of salient features in the expression peak frame. Consequently, we demonstrate how a single output from the MTSN model can be post-processed to predict both macro- and micro-expression intervals. Our results outperform the MEGC 2022 baseline method significantly by achieving an overall F1-score of 0.2586 and also did remarkably well on the MEGC 2021 benchmark with an overall F1-score of 0.3620 and 0.2867 on CAS(ME)2and SAMM Long Videos, respectively. © 2022 IEEE. All rights reserved.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Development of Smart Beehive Frame for Multi-Parameter Monitoring

Development of Smart Beehive Frame for Multi-Parameter Monit...

引用

International Conference on Microelectronics, MIEL

作者： M. Milovanović J. Pejić P. Pejić Department of Electronics Faculty of Electronic Engineering University of Niš Niš Serbia Department of Computer Science Faculty of Sciences and Mathematics University of Niš Niš Serbia Faculty of Information Technology Belgrade Metropolitan University

Honeybees are essential for pollination in agriculture. This paper presents a smart beehive frame for multi-parameter monitoring. The system is based on opto elements that emit IR light to the honeycomb and measure the reflection. The results showed that this kind of system can be used in practice to decrease the number of the visual on-site observations of the bee colonies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Structural plasticity-based hydrogel optical Willshaw model for one-shot on-the-fly edge learning

引用

InfoMat 2023年第4期5卷 48-59页

作者： Dingchen Wang Dingyao Liu Yinan Lin Anran Yuan Woyu Zhang Yaping Zhao Shaocong Wang Xi Chen Hegan Chen Yi Zhang Yang Jiang Shuhui Shi Kam Chi Loong Jia Chen Songrui Wei Qing Wang Hongyu Yu Renjing Xu Dashan Shang Han Zhang Shiming Zhang Zhongrui Wang Department of Electrical and Electronic Engineering The University of Hong KongHong Kongthe People's Republic of China ACCESS-AI Chip Center for Emerging Smart Systems InnoHK CentersHong Kong Science ParkHong Kongthe People's Republic of China School of Computer Science and Engineering Faculty of Innovation EngineeringMacao University of Science and TechnologyMacaothe People's Republic of China Key Laboratory of Microelectronics Devices and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijingthe People's Republic of China Collaborative Innovation Center for Optoelectronic Science Technology International Collaborative Laboratory of 2D Materials for OptoelectronicsScience and Technology of Ministry of EducationInstitute of Microscale OptoelectronicsShenzhen UniversityShenzhenthe People's Republic of China School of Microelectronics Southern University of Science and TechnologyShenzhenthe People's Republic of China Microelectronics Thrust Function Hub of the Hong Kong University of Science and Technology(Guangzhou)Guagndongthe People's Republic of China

Autonomous one-shot on-the-fly learning copes with the high privacy,small dataset,and in-stream data at the *** such learning on digital hardware suffers from the well-known von-Neumann and scaling *** optical neural networks featuring large parallelism,low latency,and high efficiency offer a promising ***,ex-situ training of conventional optical networks,where optical path configuration and deep learning model optimization are separated,incurs hardware,energy and time overheads,and defeats the advantages in edge ***,we introduced a bio-inspired material-algorithm co-design to construct a hydrogel-based optical Willshaw model(HOWM),manifesting Hebbian-rule-based structural plasticity for simultaneous optical path configuration and deep learning model optimization thanks to the underlying opto-chemical *** first employed the HOWM as an all optical in-sensor AI processor for one-shot pattern classification,association and *** then leveraged HOWM to function as a ternary content addressable memory(TCAM)of an optical memory augmented neural network(MANN)for one-shot learning the Omniglot *** HOWM empowered one-shot on-the-fly edge learning leads to 1000boost of energy efficiency and 10boost of speed,which paves the way for the next-generation autonomous,efficient,and affordable smart edge systems.

关键词： associative memory hydrogel one-shot learning optical neural network structural plasticity Willshaw model

来源：评论

学校读者我要写书评

暂无评论

Ternary Spike-based Neuromorphic Signal Processing System

arXiv

引用

arXiv 2024年

作者： Wang, Shuai Zhang, Dehao Belatreche, Ammar Xiao, Yichen Qing, Hongyu Wei, Wenjie Zhang, Malu Yang, Yang Department of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Department of Computer and Information Sciences Faculty of Engineering and Environment Northumbria University Newcastle upon TyneNE1 8ST United Kingdom

Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fields, resulting in significant enhancements in performance. However, DNNs generally require substantial computational resources, leading to significant economic costs and posing challenges for their deployment on resource-constrained edge devices. In this study, we take advantage of spiking neural networks (SNNs) and quantization technologies to develop an energy-efficient and lightweight neuromorphic signal processing system. Our system is characterized by two principal innovations: a threshold-adaptive encoding (TAE) method and a quantized ternary SNN (QT-SNN). The TAE method can efficiently encode time-varying analog signals into sparse ternary spike trains, thereby reducing energy and memory demands for signal processing. QT-SNN, compatible with ternary spike trains from the TAE method, quantifies both membrane potentials and synaptic weights to reduce memory requirements while maintaining performance. Extensive experiments are conducted on two typical signal-processing tasks: speech and electroencephalogram recognition. The results demonstrate that our neuromorphic signal processing system achieves state-of-the-art (SOTA) performance with a 94% reduced memory requirement. Furthermore, through theoretical energy consumption analysis, our system shows 7.5× energy saving compared to other SNN works. The efficiency and efficacy of the proposed system highlight its potential as a promising avenue for energy-efficient signal processing. © 2024, CC BY-NC-SA.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Design and Control of a Two Switch Forward Converter with Supertwisting Sliding Mode

Design and Control of a Two Switch Forward Converter with Su...

引用

International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Korhan Kayisli Ruhi Zafer Caglayan Resul Coteli Mariacristina Roscia Abdelkader Harrouz Abdelhakim Belkaid Electrical-Electronic Engineering Engineering Faculty Gazi University Ankara Turkiye Electrical- Electronic Engineering Engineering Faculty Computer Engineering Engineering Faculty Gazi University TED University Ankara Türkiye Dept. of Energy Systems Eng. Technology Faculty Firat University Elazig Turkiye University of Bergamo Bergamo Italy Dept. of Hydrocarbon and Renewable energy LDDI laboratory Ahmed Draia University Adrar Algeria Dept. of Electrical Engineering University of Bejaia Bejaia Algeria

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

This paper presents the design and control of a two-switch forward converter utilizing a supertwisting sliding mode control (STSMC) strategy. The two-switch forward converter, known for its efficiency in medium-power applications, is equipped with a robust control method to ensure improved stability and dynamic performance under varying operating conditions. The supertwisting sliding mode approach is chosen for its ability to mitigate chattering effects, a common drawback in traditional sliding mode control, while ensuring precise tracking and disturbance rejection. Through comprehensive simulation, the proposed system demonstrates enhanced performance in terms of voltage regulation and improved transient response. The results indicate that the integration of STSMC significantly improves the converter's efficiency and robustness, making it suitable for various power conversion applications.

关键词： Robust control Transient response Renewable energy sources Simulation Switches Robustness Stability analysis Power conversion Voltage control Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

IoT Enabled Bee Hive Monitoring System

IoT Enabled Bee Hive Monitoring System

引用

International Conference on Microelectronics, MIEL

Beehive monitoring can provide useful information for people associated with beekeeping to help to manage their honey bee (Apis mellifera) colonie. This paper presents the development and experimental results of a IoT...

关键词：

来源：评论

学校读者我要写书评

暂无评论

Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting

Single Block Encoder-Decoder Transformer Model for Multi-Ste...

引用

IEEE Symposium on computers & Informatics (ISCI)

作者： Mas Omar Fitri Yakub Mohamad Sofian Abu Talip Mohd Nazmin Maslan Vijay Kumar Sinha Muljono Muljono WEE Laboratory Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Department of Electronic System Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Faculty of Industrial and Manufacturing Technology and Engineering Universiti Teknikal Malaysia Melaka Malaysia Department of Computer Science & Engineering School of Engineering & Technology Chitkara University Himachal Pradesh India Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350353853

ISBN: (纸本)9798350353860

Accurate traffic flow forecasting is crucial for managing and planning urban transportation systems. Despite the widespread use of sequence modelling models like Long Short-Term Memory (LSTM) for this purpose, the potential of Transformer models remains underexplored. This is particularly true for the simplest form of a single block encoder-decoder Transformer model, which can be finely tuned through optimised hyperparameters. This paper examines the performance of a singular horizon-step forecasting method for multi-step traffic flow forecasting using a proposed Single Block Encoder-Decoder Transformer model optimised with a Grid Search algorithm. Results demonstrate that this model can enhance forecasting accuracy compared to the state-of-the-art LSTM model typically used for multi-step forecasting. The model effectively captures long-range temporal dependencies within a single road traffic flow dataset. It was tested on hourly traffic flow data to forecast the next 24 hours for the I5-North freeway in California, sourced from the Caltrans Performance Measurement System. The optimal configuration included an embedding dimension of 32, a feed-forward dimension of 128, and 8 attention heads. Results show a significant improvement, with a 4.7% reduction in Root Mean Squared Error compared to an LSTM model with two hidden layers of 100 neurons each, showcasing the potential of Single Block Encoder-Decoder Transformer models for real-world traffic prediction applications.

关键词： Accuracy Neurons Transportation Predictive models Traffic control Transformers Road traffic

来源：评论

学校读者我要写书评

暂无评论

Hybrid Machine Learning Approach for Enhanced Vulnerability Detection in Cloud Environments Using NIST and MITRE Frameworks 5

Hybrid Machine Learning Approach for Enhanced Vulnerability ...

引用

5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Lasantha, N W Chanaka Maduranga, M.W.P. Abeysekara, Ruvan Tilwari, Valmik Chakraborty, Nilotpal Sharma, Debashree Iic University of Technology Faculty of Graduate Studies Phnom Penh Cambodia University of Sri Jayewardenepura Department of Electrical and Electronic Engineering Nugegoda Sri Lanka Bcas Campus Faculty of Computing Colombo Sri Lanka Indian Institute of Information Technology Department of Computer Science Engineering Guwahati India Indian Institute of Information Technology Department of Electronics & Communication Engineering Guwahati India

ISBN: (纸本)9798331530983

Cloud security is challenged by constant adaptive cyber threats and traditional detection methods lack real time adaptability. In this paper, we propose a new hybrid ML approach stitching data from National Institute of Standards and technology (NIST) and MITRE Adversarial Tactics, Techniques and Common Knowledge (ATT&CK) databases together. In contrast to existing methods, this framework combines, in unique and unprecedented fashion, ensemble ML models and Realtime data processing for increased detection accuracy and reduced false positives. This approach addresses specific challenges in the cloud environments and by leveraging standardised frameworks, it offers actionable audiences for efficient and effective vulnerability management process. The framework is validated by the experimental results which prove its robustness to evolution of the cybersecurity demands. © 2025 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

Watermarking and Encryption for electronic Medical Records (EMR) Security Based on mCloud 2

Watermarking and Encryption for Electronic Medical Records (...

引用

2nd International Conference on Cyber Resilience, ICCR 2024

作者： Abdulshaheed, Haider Rasheed Abbas, Yaseen Saadi Tawfeq, Jamal F. Ateeq, Karamath Alnawayseh, Saif. E. A. Ghazal, Taher M. Baghdad College Of Economic Sciences University Computer Engineering Techniques Department Baghdad Iraq College Of Engineering Al-Nahrain University Electronic And Communications Engineering Department Baghdad Iraq Medical Technical College Al-Farahidi University Department Of Medical Instrumentation Technical Engineering Baghdad10070 Iraq School Of Computing Skyline University College University City Sharjah Sharjah United Arab Emirates College Of Engineering Mutah University Department Of Electrical Engineering Al-Karak Jordan Khalifa University Centre For Cyber Physical Systems Computer Science Department United Arab Emirates Center For Cyber Security Faculty Of Information Science And Technology Selangor Bangi43600 Malaysia

ISBN: (纸本)9798350394962

Providing quality healthcare services and promoting collaborative clinical research are easier and more efficient with electronic medical record (EMR) systems. All aspects of care are included in electronic health records. Data characterized by volume, variety, and velocity is what IBM defines as big data. Therefore, we evidently have a significant problem managing 'big EMR data' from a volume, accuracy, and velocity perspective. Data misuse and patient safety are significant risks associated with poorly implemented EMR-based systems. Storage, access, and retrieval of big data are all aspects of security to consider. Location is another important aspect of secure data use, in addition to strong access control mechanisms. Researchers are investigating secure mobile data usage based on location after recent reports of illegal trade and theft of patient data over mobile devices. To improve work flow dynamics and efficiency, healthcare facilities are increasingly using mobile devices. In spite of this, mobile devices are becoming more and more common. A new technique for preventing EMR infiltration and manipulation by hackers using the cloud is presented in this article. © 2024 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

A systematic review of ulcer detection methods in wireless capsule endoscopy

引用

Informatics in Medicine Unlocked 2024年 51卷

作者： Musha, Ahmmad Hasnat, Rehnuma Mamun, Abdullah Al Hossain, Md Sohag Hossen, Md Jakir Ghosh, Tonmoy Department of Electrical and Electronic Engineering Pabna University of Science and Technology Bangladesh Department of Electrical and Computer Engineering Oakland University United States School of Information and Communication Technology Griffith University Brisbane Australia Faculty of Engineering and Technology Multimedia University Malaysia Department of Electrical and Computer Engineering The University of Alabama Tuscaloosa AL United States Department of Electrical and Electronic Engineering Feni University Feni Bangladesh

Background: Ulcers are one of the most prevalent disorders in the gastrointestinal (GI) tract, affecting many people worldwide. Wireless capsule endoscopy (WCE) emerges as the most non-invasive way to diagnose ulcers in the GI tract. However, manually reviewing images captured by WCE is a tedious and time-consuming process. Implementing a computer-aided ulcer detection system can facilitate the automatic evaluation of these images. Methods: Many researchers have proposed various models to develop automatic ulcer detection methods. This research aims to conduct a systematic review by scouring four repositories (Scopus, PubMed, IEEE Xplore, and ScienceDirect) for all original publications on computer-aided ulcer detection published between 2011 and 2024. The review follows the the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Results: The full texts of 89 scientific articles were reviewed. The contributions of this paper are two-fold: I) it reports and summarizes the current state-of-the-art ulcer detection algorithms;and II) it finds the most appropriate and preferable method in terms of color space, region of interest selection, feature extraction, and classifier. Conclusion: The paper concludes with a discussion of the challenges and futuredirections for ulcer detection. © 2024 The Authors

关键词：

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：