检索结果-内蒙古大学图书馆

2022 15th International Conference on computer and Electrical engineering, ICCEE 2022

作者： Yi, Li Jinguo, Li Yongjie, Zhai Ping, Meng College of Computer Science and Technology Shanghai University of Electric Power Shanghai200000 China School of Control and Computer Engineering North China Electric Power University Baoding Hebei071000 China

In view of the low detection efficiency of traditional aerial image-based self-explosive insulators and the need to manually extract the features of self-explosive insulators, a self-explosive insulator detection algorithm based on the improved YOLO v4 is proposed: We use the hybrid data augmentation method to increase the number of defective samples of self-explosive insulators and increase the diversity of self-explosive insulators to improve the detection accuracy of the algorithm. In addition, the channel attention mechanism is combined with the YOLO v4 algorithm to improve the feature extraction capability of algorithms to self-explosion insulators. The proposed algorithm is verified using the expanded self-explosive insulator dataset and the traffic signs dataset TT100K. The experimental results show that the proposed algorithm has a mAP of 92.0 % on the self-explosive insulator dataset and has an F1-score of 78.70% on TT100K dataset, which has positive significance for the research on self-explosive insulator detection. © 2022 Published under licence by IOP Publishing Ltd.

关键词： Explosives

来源：评论

学校读者我要写书评

暂无评论

Adaptive Global-local Fusion Network Based Deep Unsupervised Hashing for Remote Sensing Image Retrieval

Adaptive Global-local Fusion Network Based Deep Unsupervised...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Zekun Xu Yipeng Zhou Quan Z. Sheng Chao Li Tongtong Lou Weipeng Jing College of Computer and Control Engineering Northeast Forestry University Harbin China School of Computing Macquarie University Sydney Australia

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Unsupervised hashing methods have gained wide-spread popularity for remote sensing (RS) image retrieval due to their high efficiency. Existing methods heavily rely on similarity matrix generated by pre-trained models as supervised signals. However, such pre-trained models obtained from natural images fail to comprehensively extract features in RS images, yielding unreliable similarity relationships. Considering complex features in RS images, we propose a novel adaptive global-local fusion network based deep unsupervised hashing (AFDUH) method. The advantages of AFDUH lie in the use of large kernel convolution and bi-level routing attention mechanism for learning local and global features simultaneously. AFDUH fuses these features under different resolutions in an interactive fashion to deduce high-quality similarity matrix based on contrastive learning. Besides, we embed a sample selection strategy in AFDUH, which can filter out unreliable supervised signals to further improve retrieval accuracy. Extensive experiments on two RS datasets demonstrate that AFDUH outperforms the state-of-the-art baselines.

关键词： Adaptation models Adaptive systems Accuracy Image retrieval Feature extraction Transformers Routing

来源：评论

学校读者我要写书评

暂无评论

Research on Task Scheduling Algorithms for Cloud-Edge Collaboration 19th

Research on Task Scheduling Algorithms for Cloud-Edge Collab...

引用

19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Lu, Shuai Zhou, Haibo Zhao, Shuaishuai Xu, Wangbei Fang, Kai Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China College of Mathematics and Computer Sciences Zhejiang A&F University Hangzhou311300 China

ISBN: (纸本)9783031651229

With the advent of the 5G era, the development of IoT technology has been accelerated. Due to the continuous increase in the amount of data waiting to be processed from the edge, edge nodes may struggle to handle such a vast amount of data. Therefore, the technology of cloud-edge collaboration has emerged, and how to achieve cloud-edge collaborative task scheduling has become a current research hotspot. This article provides a detailed exposition of the relevant work on task scheduling in the cloud-edge environment, and outlines the common optimization objectives in the cloud-edge collaboration scenario. The methods used to solve task scheduling problems are classified and summarized, including heuristic, heuristic algorithm based on linear programming, and meta-heuristic algorithms. The advantages and disadvantages of each algorithm are analyzed. Finally, the development trends of large-scale task scheduling in the cloud-edge environment are discussed, providing valuable insights for achieving real-time performance, efficiency, and energy conservation in the Internet of Things. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

引用

Congress on Evolutionary Computation

作者： Wenqiang Ma Yaqing Hau Hua Yu Xiangrong Tong Zexuan Zhu Qiang Zhang School of Computer Science and Technology Dalian University of Technology Dalian China School of Computer and Control Engineering Yantai University Yantai China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Deep neural networks are powerful and popular learning models; however, recent studies have shown that deep neural network-based policies are susceptible to deception by adversarial attacks. A minimalistic attack is a specialized form of adversarial attack that aims to accomplish successful attacks at the lowest possible cost. Recently, transfer optimization algorithms have been applied to deceive previously trained policies by acquiring knowledge from previously solved tasks. Experiments indicate that the transfer optimization algorithms perform well compared to traditional optimization algorithms. However, current transfer algorithms for addressing minimalistic attacks not only select a single source task for knowledge transfer but also tend to overly rely on identified appropriate source tasks. To address this issue, this paper introduces a similar locality based transfer evolutionary optimization algorithm. It can adaptively select multiple source tasks and extract valuable knowledge from these source tasks. Moreover, by leveraging the concept of similar locality, the algorithm alleviates its excessive dependence on familiar tasks, thereby providing fresh knowledge for the optimization of the target task. On this basis, the algorithm can mine more valuable knowledge from the large source task space to achieve a successful attack in a shorter period. The algorithm is tested on three Atari games-BeamRider, Qbert, and Seaquest-demonstrating its ability and potential to outperform other transfer optimization algorithms currently available in solving this problem.

关键词： Sociology Fitting Optimization methods Games Reinforcement learning Security Task analysis

来源：评论

学校读者我要写书评

暂无评论

MemSAM: Taming Segment Anything Model for Echocardiography Video Segmentation

MemSAM: Taming Segment Anything Model for Echocardiography V...

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Xiaolong Deng Huisi Wu Runhao Zeng Jing Qin College of Computer Science and Software Engineering Shenzhen University College of Mechatronics and Control Engineering Shenzhen University Centre for Smart Health School of Nursing The Hong Kong Polytechnic University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

We propose a novel echocardiographical video segmentation model by adapting SAM to medical videos to address some long-standing challenges in ultrasound video segmentation, including (1) massive speckle noise and artifacts, (2) extremely ambiguous boundaries, and (3) large variations of targeting objects across frames. The core technique of our model is a temporal-aware and noise-resilient prompting scheme. Specifically, we employ a space-time memory that contains both spatial and temporal information to prompt the segmentation of current frame, and thus we call the proposed model as MemSAM. In prompting, the memory carrying temporal cues sequentially prompt the video segmentation frame by frame. Meanwhile, as the memory prompt propagates high-level features, it avoids the issue of misidentification caused by mask propagation and improves representation consistency. To address the challenge of speckle noise, we further propose a memory reinforcement mechanism, which leverages predicted masks to improve the quality of the memory before storing it. We extensively evaluate our method on two public datasets and demonstrate state-of-the-art performance compared to existing models. Particularly, our model achieves comparable performance with fully supervised approaches with limited annotations. Codes are available at https://***/dengxl0520/MemSAM.

关键词： Image segmentation Adaptation models computer vision Ultrasonic imaging Echocardiography Annotations Noise

来源：评论

学校读者我要写书评

暂无评论

Speed Regulation of Converter-Driven DC Motors Via a Discrete-Time Reduced-Order GPIO with Genetic Algorithm 4

Speed Regulation of Converter-Driven DC Motors Via a Discret...

引用

4th International Conference on Communication, Information and Computing Technology, ICCICT 2021

作者： Vikhe, P.S. Tiwary, N.K. Kadu, C.B. Mandhare, V.V. Jadhav, V.K. Department Instrumentation & Control Engineering Pravara Rural Engineering College Loni India Department of Computer Engineering Pravara Rural Engineering College Loni India Department Instrumentation & Control Engineering Pravara Rural Engineering College Loni India

ISBN: (纸本)9781665404303

The aim of this work is to design a speed controller for DC motor tuning PID controller. To obtain an output with minimum errors, PID parameters are selected using bio-inspired optimization technique of Genetic Algorithm. The system with second order is used to control the speed. This work deals with optimization approach based on bio-inspired in controllers and its merits over traditional is discussed and implemented with help of MATLAB Simulink. DC motor is interfaced to Arduino via Motor driver circuitry. Discrete-Time Reduced-Order GPIO with Genetic algorithm computes parameter of PID controller. Thus, Arduino controls DC motor according to computed parameters. The optimization technique putforward in this work can also be applicable for systems having higher order, to provide effective system output having minimum errors. ©2021 IEEE

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach

Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual...

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Wei Dong Xing Zhang Bihui Chen Dawei Yan Zhijun Lin Qingsen Yan Peng Wang Yang Yang School of Computer Science and Engineering University of Electronic Science and Technology of China College of Information and Control Engineering Xi'an University of Architecture and Technology School of Computer Science Northwestern Polytechnical University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Parameter-efficient fine-tuning for pre-trained Vision Transformers aims to adeptly tailor a model to downstream tasks by learning a minimal set of new adaptation parameters while preserving the frozen majority of pre-trained parameters. Striking a balance between retaining the generalizable representation capacity of the pre-trained model and acquiring task-specific features poses a key challenge. Currently, there is a lack of focus on guiding this delicate trade-off. In this study, we approach the problem from the perspective of Singular Value Decomposition (SVD) of pre-trained parameter matrices, providing insights into the tuning dynamics of existing methods. Building upon this understanding, we propose a Residual-based Low-Rank Rescaling (RLRR) fine-tuning strategy. This strategy not only enhances flexibility in parameter tuning but also ensures that new parameters do not deviate excessively from the pre-trained model through a residual design. Extensive experiments demonstrate that our method achieves competitive performance across various downstream image classification tasks, all while maintaining comparable new parameters. We believe this work takes a step forward in offering a unified perspective for interpreting existing methods and serves as motivation for the development of new approaches that move closer to effectively considering the crucial trade-off mentioned above. Our code is available at https://***/zstarN70/***.

关键词： computer vision Adaptation models Codes Buildings Transformers Pattern recognition Matrix decomposition

来源：评论

学校读者我要写书评

暂无评论

A Data Transmission Approach Based on Ant Colony Optimization and Threshold Proxy Re-encryption in WSNs

引用

Journal of Artificial Intelligence and Technology 2022年第1期2卷 23-31页

作者： Jing Liu Zenghui Liu Chenyu Sun Junxi Zhuang College of Computer Science Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of EducationBeijing 100124China College of Automation Engineering Beijing PolytechnicBeijing 100176China

Wireless sensor networks(WSNs)have become increasingly popular due to the rapid growth of the Internet of *** open wireless transmission media are easy to attack,security is one of the primary design concerns for *** solutions consider routing and data encryption as two isolated issues,providing incomplete ***,in this paper,we divide the WSN communication process into a data path selection phase and a data encryption *** propose an improved transmission method based on ant colony optimization(ACO)and threshold proxy re-encryption for WSNs,and we named it as *** method resists internal and external attacks and ensures safe and efficient data *** the data path selection stage,the ACO algorithm is used for network *** improvement of the pheromone concentration is *** order to resist attacks from external attackers,proxy re-encryption is extended to WSN in the data encryption *** threshold secret sharing algorithm is introduced to generate a set of re-encryption key fragments composed of random numbers at the source *** confirm the performance of our model via simulation studies.

关键词： wireless sensors network ant colony optimization pheromone proxy re-encryption threshold

来源：评论

学校读者我要写书评

暂无评论

A New Cerebellar control Scheme and Simulation Based on Kalman Estimator

引用

Chinese Journal of Electronics 2023年第2期18卷 297-301页

作者： Shaobai Zhang Xiaogang Ruan Xiefeng Cheng College of Computer Nanjing University of Posts and Telecommunications Nanjing China College of Electronic Information and Control Engineering Beijing University of Technology Beijing China

The present paper proposes a new cerbellar learning scheme of feedback error learning scheme for tracing in motor control system. In the scheme, the model of cerebellar cortex is regarded as the feedforward controller. Specifically, a neural network and an estimator are adopted in the cerebellar cortex model which can predict the future state and eliminate faults caused by time delay. Then the new scheme was used to control inverted pendulum. The simulation experimental results show that the new scheme can learn to control the inverted pendulum for tracing successfully.

关键词： Motor drives Adaptation models Simulation Neural networks Optical fiber networks Brain modeling Telecommunications

来源：评论

学校读者我要写书评

暂无评论

Modified Blood Oxygen Levels Detection

Modified Blood Oxygen Levels Detection

引用

International Conference on Electrical, control and Instrumentation engineering (ICECIE)

作者： Sai Sunil Kumar RK M. Ananthi T. Mangayarkarasi Jaya Darshini G Kalaivani U V Computer Science and Business Systems Sri Sairam Engineering College Chennai India Instrumentation and Control Engineering Sri Sairam Engineering College Chennai India

A gadget called an OXIMETER is used to measure blood oxygen levels. The oximeter does not produce correct results in people with scleroderma, those who have decreased tissue perfusion, such as is the case in anemia instances, and people who have digital ulcers. Scleroderma is an autoimmune illness in which the body attacks its own cells because it believes they are foreign invaders, making the skin rough and making it difficult to accurately measure blood oxygen levels. OXILASER is a gadget that combines an oximeter and a laser. The laser aids in penetrating through rough skin to easily and accurately measure blood oxygen levels.

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：