检索结果-内蒙古大学图书馆

Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network

computers, Materials & Continua 2023年第7期76卷 1213-1247页

作者： Muhammad Rizwan Sana Ul Haq Noor Gul Muhammad Asif Syed Muslim Shah Tariqullah Jan Naveed Ahmad Department of Electronics University of PeshawarPeshawar25120Pakistan Department of Electronics Engineering Korea Polytechnic UniversitySiheungKorea Department of Electrical Engineering Capital University of Science and TechnologyIslamabad44000Pakistan Department of Electrical Engineering University of Engineering and TechnologyPeshawar25120Pakistan Department of Computer Science Prince Sultan UniversityRiyadh11586Saudi Arabia

Appearance-based dynamic Hand Gesture Recognition(HGR)remains a prominent area of research in Human-computer Interaction(HCI).Numerous environmental and computational constraints limit its real-time *** addition,the performance of a model decreases as the subject’s distance from the camera *** study proposes a 3D separable Convolutional Neural Network(CNN),considering the model’s computa-tional complexity and recognition *** 20BN-Jester dataset was used to train the model for six gesture *** achieving the best offline recognition accuracy of 94.39%,the model was deployed in real-time while considering the subject’s attention,the instant of performing a gesture,and the subject’s distance from the *** being discussed in numerous research articles,the distance factor remains unresolved in real-time deployment,which leads to degraded recognition *** the proposed approach,the distance calculation substantially improves the classification performance by reducing the impact of the subject’s distance from the ***,the capability of feature extraction,degree of relevance,and statistical significance of the proposed model against other state-of-the-art models were validated using t-distributed Stochastic Neighbor Embedding(t-SNE),Mathew’s Correlation Coefficient(MCC),and the McNemar test,*** observed that the proposed model exhibits state-of-the-art outcomes and a comparatively high significance level.

关键词： 3D separable CNN computational complexity hand gesture recognition human-computer interaction

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Action Recognition Using Spatiotemporal, Adaptive, and Attention-Guided Refining-Network

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第6期6卷 1460-1471页

作者： Yin, Xinpeng Zhang, Cheng Huang, ZiXu He, Zhihai Cao, Wenming Shenzhen University State Key Laboratory of Radio Frequency Heterogeneous Integration Department of Electronics and Information Engineering Shenzhen518060 China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen518055 China

Previous articles on unsupervised skeleton-based action recognition primarily focused on strategies for utilizing features to drive model optimization through methods like contrastive learning and reconstruction. However, designing application-level strategies poses challenges. This article shifts the focus to the generation-level modelings and introduces the spatiotemporal adaptively attentions-guided refining network (AgRNet). AgRNet approaches the reduction of costs and enhancement of efficiency by constructing the adaptive activity-guided attention (AAGA) and adaptive dominant-guided attenuation (ADGA) modules. The AAGA leverages the sparsity of the correlation matrix in the attention mechanism to adaptively filter and retain the active components of the sequence during the modeling process. The ADGA embeds the local dominant features of the sequence, obtained through convolutional distillation, into the globally dominant features under the attention mechanism, guided by the defined attenuation factor. Additionally, the progressive feature modeling (PFM) module is introduced to complement the progressive features in motion sequences that were overlooked by AAGA and ADGA. AgRNet shows efficiency on three public datasets, NTU-RGBD 60, NTU-RGBD 120, and UWA3D. © 2020 IEEE.

关键词： Time series analysis

来源：评论

学校读者我要写书评

暂无评论

4D-Rossler Hyperchaotic System for Image Encryption and Decryption with High Security 10

4D-Rossler Hyperchaotic System for Image Encryption and Decr...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Agarwal, Soumil Byramdharmika, M. Dhathri, Sree Thanikaiselvan, V. Subashanthini, S. Amirtharajan, Rengarajan Vellore Institute of Technology School of Electronics Engineering Vellore India Engineering and Information Systems Vellore Institute of Technology School of Computer Science Vellore India Sastra Deemed University School of Electrical & Electronics Engineering Thanjavur India

ISBN: (纸本)9798350353068

In today's digital world, safeguarding data at all times is important, especially with the widespread use of images across various processes. Image encryption is vital in concealing sensitive information through cryptographic techniques, rendering data indecipherable to unauthorized parties. However, existing encryption systems often fall short in terms of both efficiency and security. This research explores chaos theory for image encryption methodologies to address these limitations. A comprehensive study of image encryption fundamentals was conducted, including chaos theory, various chaotic maps, DNA encoding, and encryption system evaluation metrics. Implementation of different chaotic maps such as the logistic map, tent map, and combined logistic-tent map, along with 3D chaotic systems like the Lorenz and Rossler systems, was performed for encryption purposes. Additionally, the 4D extension of the Rossler hyperchaotic system was introduced for enhanced encryption capabilities. Encryption methods were evaluated using metrics such as UACI, NPCR, correlation coefficients, image entropy and histogram analysis, with results compared and tabulated. This research advances image encryption techniques by leveraging chaos theory to achieve heightened security and efficiency in safeguarding image data. © 2024 IEEE.

关键词： Chaotic systems

来源：评论

学校读者我要写书评

暂无评论

Solar Energy based Smart Home Monitoring and Automation using IOT 4

Solar Energy based Smart Home Monitoring and Automation usin...

引用

4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Dharmaraj, N. Adithyaa, A. Satyanarayanaa, H. Mouleesh, Y. Rupesh, S. Priyadharshini, K. Rajalakshmi Institute of Technology Dept. of Electronics and Communication Engineering Chennai India Rajalakshmi Institute of Technology Dept. of Computer and Communication Engineering Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508845

In the pursuit of sustainable living and energy efficiency, integrating renewable energy sources with smart home technologies has become increasingly important. This paper presents a novel system that utilizes solar energy as the primary power source for a smart home, combined with Internet of Things (IoT) technology for monitoring and automation. The primary goal of this project is to reduce waste in conventional ways by making extensive use of energy recovery sources, enhancing safety, and removing environmental impact. Optimizing the equipment's use of program energy in accordance with the actual time of solar power generation is one of the key goals. Another is enhancing the effectiveness of energy transfer through remote monitoring and control using data and smartphone applications. The integration of Internet of Things (IOT) technology with solar energy systems is critical to the sustainability, efficiency, and administration of residential surroundings. This article investigates the deployment capabilities of the Internet of Things (IOT) for solar household energy system automation and monitoring. Future house automation will rely on solar energy and Internet of Things monitoring technologies once this work is completed. © 2024 IEEE.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

Outage Analysis of Multiple IRS-aided Cooperative NOMA System 15

Outage Analysis of Multiple IRS-aided Cooperative NOMA Syste...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Murugadass, Arthi Kumaravelu, Vinoth Babu Kennedy, Helen Sheeba John Anjana, B.S. Dipinkrishnan, R. Bilim, Mehmet Vellore Institute of Technology School of Computer Science and Engineering Chennai India Vellore Institute of Technology School of Electronics Engineering Department of Communication Engineering Vellore India Nuh Naci Yazgan University Department of Electrical and Electronics Engineering Kayseri Turkey

ISBN: (纸本)9798350370249

The traditional cooperative non-orthogonal multiple access (CNOMA) technique improves the outage and data rate performance for cell-edge users, albeit at the expense of near users. Due to the ability to control the propagation environment, introducing intelligent reflective surfaces (IRS) into a multi-user network can reduce costs, signal processing complexity, and energy consumption. In this work, a comprehensive downlink framework for a blind-IRS-supported CNOMA system is established to enhance outage performance for both cell-edge and near users. The closed-form analytical expressions for the outage probability of the near and cell-edge users within this proposed system are derived. Furthermore, these analytical expressions are validated through Monte-Carlo simulations. The cell-edge user of our proposed model outperforms traditional NOMA and IRS-assisted NOMA variants. To achieve a target outage probability of 10-3, our proposed system requires ∼ 4 dB lower signal-to-noise ratio (SNR) compared to other IRS-assisted NOMA variants. © 2024 IEEE.

关键词： Image coding

来源：评论

学校读者我要写书评

暂无评论

Review On the Techniques Used for Detection of Fabric Defects Using AI 1

Review On the Techniques Used for Detection of Fabric Defect...

引用

1st IEEE International Conference on Advances in electronics, Communication, Computing and Intelligent Information Systems, ICAECIS 2023

作者： Batra, Isheeta Prasad, S A Hari Arvind, K.S. Faculty of Engineering & Technology Department of Computer Science and Engineering Karnataka India Faculty of Engineering & Technology Department of Electronics and Communication Engineering Karnataka India

ISBN: (纸本)9798350348057

The garment industry is the second-most polluting industry after oil. These mass-produced clothes if rejected are dumped and have an enormous impact on the environment. Therefore, to save the cost post production it is important to identify any sorts of defects pre-production when clothes are in a textile form, so that in case the fabric lacks somewhere in quality it can always be replaced, saving all the time and cost. This detection is possible using techniques like segmentation, or on the basis of texture or by using deep learning algorithms each having its own advantages and disadvantages to efficiently identify the defects in textile fabric. This paper is a comprehensive study of these three techniques and comparison made on basis of brief analysis which say that the deep learning technique is the best of the three for detection of defects keeping in contrast the type of research and developing technologies. © 2023 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

引用

computer Systems Science & engineering 2022年第9期42卷 935-948页

作者： M.Manikandan R.Subramanian M.S.Kavitha S.Karthik Department of Computer Science&Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatore641035India Department of Computer Science&Engineering SNS College of TechnologyCoimbatore641035India

In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.

关键词： Cost effectiveness hybrid cloud optimal task scheduling virtual machine resource allocation make span

来源：评论

学校读者我要写书评

暂无评论

Movie Sense—Hybrid Movie Recommendation System with Sentimental Analysis 3rd

Movie Sense—Hybrid Movie Recommendation System with Sentime...

引用

3rd International Conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Sudhane, G. Sai Rao, G. Venkateswara Vani, V. Karthik, N. Department of Electrical and Electronics Engineering Puducherry India Department of Computer Science and Engineering National Institute of Technology Puducherry Puducherry Karaikal609609 India

ISBN: (纸本)9789819783540

Post-pandemic, with the advent of many OTT platforms, there are a number of different movies and web series available which makes it difficult for the users to find a suitable movie to watch. So the movie recommendation system helps the users by recommending some movies based on their past search history, their interests and also considering the movie genre, actors, director and movie ratings. Our system uses a hybrid filtering technique which makes the system suitable for new users as well by considering the interests of various other users using SVD. Sentimental Analysis is done using a Sentiment Intensity Analyzer (SIA). Since it uses the most accurate methods, it makes the system a robust one. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Marine Life Analysis Based on Ocean Water Level Rise and Climate Change Using Underwater Imaging Techniques

引用

Remote Sensing in Earth Systems Sciences 2024年第4期7卷 657-669页

作者： Mate, Anuja Dinesh Arulananth, T.S. Sathiya, T. Jyothi, B. Swarna Raja, A. Wasim Yalawar, Mrutyunjaya S. Computer Technology Sou.Venutai Chavan Polytechnic Pune India Department of Electronics and Communication Engineering MLR Institute of Technology Telangana Hyderabad 500043 India Department of Computer Science and Engineering Sona College of Technology Tamil Nadu Salem India Computer Science & amp Engineering Madanapalle Institute of Technology & amp Science Andhra Pradesh Madanapalle India Artificial Intelligence and Data Science Sri Krishna College of Engineering and Technology Coimbatore India Department of Computer Science and Engineering CMR Engineering College Hyderabad India

Forecasting sea levels is crucial for harbour operations and coastal structure design. The oceans make up two-thirds of Earth’s surface;therefore, historically, the marine economy has been extremely diversified as well as abundant. In order to explore as well as harness this difficult environment, prominent businesses and ecological groups are developing and deploying novel gadgets backed by state-of-the-art marine mechatronics solutions. This research proposes a novel method of marine life monitoring with ocean water level rise analysis based on climate changes by underwater imaging using machine learning techniques. Here, the input has been collected as underwater images as well as processed for noise removal and normalisation. Then, these images were segmented for monitoring marine life using U-Net graph cut fuzzy clustering with a spatial neural network. Then this segmented image has been classified using multilayer region-based Q-belief vector neural networks for the analysis of sea level rise analysis based on climate change training. Experimental analysis has been carried out for various marine life monitoring datasets and climate change datasets in terms of training accuracy, specificity, recall, AUC, and Kappa-coefficient. Proposed techniques achieved specificity 93%, training accuracy 91%, AUC 95%, recall 96%, and Kappa-coefficient 90%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Climate changes Machine learning techniques Marine life monitoring Q-belief vector Water level rise analysis

来源：评论

学校读者我要写书评

暂无评论

An Improved Deep Structure for Accurately Brain Tumor Recognition

引用

computer Systems Science & engineering 2023年第8期46卷 1597-1616页

作者： Mohamed Maher Ata Reem N.Yousef Faten Khalid Karim Doaa Sami Khafaga Department of Communications and Electronics Engineering MISR Higher Institute for Engineering and TechnologyMansoura35516Egypt Department of Electronics and Communications Delta Higher Institute for Engineering and TechnologyMansoura35516Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Brain neoplasms are recognized with a biopsy,which is not commonly done before decisive brain *** using Convolutional Neural Networks(CNNs)and textural features,the process of diagnosing brain tumors by radiologists would be a noninvasive *** paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning *** proposed model extracts Gray Level Co-occurrence Matrix(GLCM)textural features from MRI brain tumor ***,a deep neural network(DNN)model has been proposed to select the most salient features from the ***,it manipulates the extraction of the additional high levels of salient features from a proposed CNN ***,a fusion process has been utilized between these two types of features to form the input layer of additional proposed DNN model which is responsible for the recognition *** common datasets have been applied and tested,Br35H and FigShare *** first dataset contains binary labels,while the second one splits the brain tumor into four classes;glioma,meningioma,pituitary,and no ***,several performance metrics have been evaluated from both datasets,including,accuracy,sensitivity,specificity,F-score,and training *** results show that the proposed methodology has achieved superior performance compared with the current state of art *** proposed system has achieved about 98.22%accuracy value in the case of the Br35H dataset however,an accuracy of 98.01%has been achieved in the case of the FigShare dataset.

关键词： Brain tumor convolutional neural network gray level co-occurrence matrix noninvasive FigShare dataset Br35H dataset

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：