检索结果-内蒙古大学图书馆

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Nair, Rekha R Babu, Tina Kishore, S. Shivaswamy, Smitha Aruna, S. Bhargavi, Manchikalapudi Alliance School of Advanced Computing Alliance University Department of Computer Science and Engineering Bengaluru India Department of Computer Application Karnataka Mangaluru India Acharya Institute of Technology Department of Computer Applications Bengaluru India School of Science and Computer Studies CMR University Bangalore India Hyderabad India

ISBN: (纸本)9798331518097

Emotion recognition through facial expressions and gesture analysis has emerged as a key area of research in computer vision and human-computer interaction. The ability to automatically detect and classify human emotions has wide-ranging applications, from enhancing user experiences to improving mental health monitoring and surveillance systems. This project builds on this background to develop a comprehensive system for recognizing emotions and gestures in both humans and animals. The system integrates facial emotion recognition, hand gesture interpretation, and animal emotion detection into a single platform. Using advanced deep learning models and computer vision libraries, the system classifies facial expressions into categories such as happiness, sadness, anger, fear, surprise, and neutral. The gesture recognition component interprets hand signals to convey messages like 'need help' or 'need water.' An innovative aspect of this work is the extension of emotion recognition to animals, particularly focusing on species like dogs and monkeys. Implemented primarily in Python, the system leverages libraries such as OpenCV and DeepFace. By combining these different modalities of nonverbal communication analysis, the project presents a versatile solution with potential applications in human-computer interaction, mental health monitoring, security, and animal welfare. © 2024 IEEE.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

Enhancing image feature matching detection: ORB and HDBSCAN algorithm integration 15

Enhancing image feature matching detection: ORB and HDBSCAN ...

引用

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

作者： Goel, Aadya Mishra, Pallavi Bhatia, Rachna School of Computer Science and Engineering Vellore Institute of Technology Vellore632014 India School of Advanced Sciences Vellore Institute of Technology Vellore632014 India

ISBN: (纸本)9798350370249

This research paper explores the integration of the Oriented FAST and Rotated BRIEF (ORB) algorithm and the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm to enhance image feature matching and detection. ORB, known for its speed and accuracy in key point descriptor extraction, is combined with HDBSCAN, a robust clustering technique capable of identifying complex clusters, resulting in an innovative approach for accurate and efficient feature matching. The study rigorously evaluates this hybrid method on scientific image datasets, like microscopic images, blots, and graphs. The comparative analysis demonstrates the superior performance of the ORB-HDBSCAN combination from Homography-RANSAC integration. The proposed approach exhibits significant promise in real-world applications, including similarity detection systems. The OpenCV library is used in the design and implementation of the suggested algorithm. This research provides a valuable contribution to the field of computer vision, offering an advanced solution for image feature matching that addresses the complexities of modern environments. ©2024 IEEE.

关键词： Image matching

来源：评论

学校读者我要写书评

暂无评论

Sensor Enabled Vehicle Parking System using Blynk IoT Application 5

Sensor Enabled Vehicle Parking System using Blynk IoT Applic...

引用

5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Sekar, G. Benson Mansingh, P.M. Prasad, J. Britto Manoj, A. Vsb College of Engineering Department of Electronics and Communication Engineering Technical Campus Coimbatore India Vignan's Foundation for Science Technology and Research Department of Advanced Computer science and Engineering Guntur India Kpr Institute of Engineering and technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798331504403

In the current scenario, finding the parking in full slot area is very difficult and also there is no online platform to check those parking slot availability details. The proposed system provides a parking slot availability information over phone and reducing a waiting time to check the availability. Using the 'Smart parking system' the parking slot availability can be accessed easily over the internet. This system can completely automate the entry and exit of car and also payment process. The Node MCU ESP8266 is connected with IR sensors. The IR sensors will show the availability of the parking slot. The entry and exit gates are connected with servo motors. RFID scanner used to show the information of the user while entering. Online service software was used (Blynk app) it shows the slot through your mobile world. © 2024 IEEE.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

MC-SORT: A Motion Correction-Based Framework for Long-Term Multiple Object Tracking 27

MC-SORT: A Motion Correction-Based Framework for Long-Term M...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Li, Xiangyu Qin, Yunchuan Li, Ruihui Tan, Guanghua Tang, Zhuo Li, Kenli College of Computer Science and Electronic Engineering Hunan University China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University China

ISBN: (纸本)9781643685489

Long-term occlusion is one of the most formidable challenges in Multi-Object Tracking (MOT). The motion models of existing SORT-based trackers are unreliable in estimating the motion states of long-term occluded targets. This is mainly because as the occlusion period increases, the increases speed of estimation errors in the motion model increases faster. In practical applications, we believe that the estimation error of the tracker during long-term occlusion is mainly concentrated in the estimation error of the motion model on the velocity of the occluded target. In this work, we have demonstrated that in the long-term occlusion period, appropriately correcting the estimated values of the motion model on the target motion velocity and fully utilizing the temporal and attribute information of the target's historical trajectory as calculation indicators of correlation are beneficial for improving the robustness of the tracker in long-term occlusion. We refer to our proposed motion correction-based framework as MC-SORT, which mainly consists of a Momentum Compensation Module (MCM) and a Backtracking Re-association (BRA) module. The former can correct the estimated value of the target's motion state during long-term occlusion, the latter uses the temporal and attribute information of the target's historical trajectory during long-term occlusion as correlation indicators to measure the degree of correlation between the target and trajectory. Our proposed MC-SORT has the characteristics of simplicity, online, real-time, and plug-and-play, particularly improving the robustness of the tracker in long-term occlusion. The extensive experimental results on the MOT17 and MOT20 datasets demonstrate the robustness and superiority of our framework. © 2024 The Authors.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Multi-domain Vertically Aligned LCD by Azo-Dye Photo-alignment Method

Multi-domain Vertically Aligned LCD by Azo-Dye Photo-alignme...

引用

International Conference on Display Technology, 2024

作者： Tang, Shu Tuen Chiu, Hon Wah Tseng, Man Chun Kwok, Hoi Sing State Key Laboratory on Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong

Vertically Aligned LCD is one of the most widely used optical modes in LCD TV and mobile devices. It is also a very important category of passive LC displays used in Automobiles. It has the advantages of perfect dark state and very high contrast ratio for normal viewing. However, single domain VA LCD has the intrinsic issue of dead zone (contrast vanishing zone) in certain viewing direction in the voltage-on state, which seriously limits its viewing angle performance. Recently, the State Key Laboratory on advanced Displays and Optoelectronics Technologies of the Hong Kong University of science and Technology has developed an easy-to-apply multi-domain VA LCD technology that can be readily implemented in LCD factories without major investment and change in current production process. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Azo dyes

来源：评论

学校读者我要写书评

暂无评论

Segment differential aggregation representation and supervised compensation learning of ConvNets for human action recognition

引用

science China(Technological sciences) 2024年第1期67卷 197-208页

作者： REN ZiLiang ZHANG QieShi CHENG Qin XU ZhenYu YUAN Shuai LUO DeLin School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin 541004China Department of the mechanical engineering Erlangen-Nuremberg UniversityErlangen 91508Germany School of Aerospace Engineering Xiamen UniversityXiamen 361102China

With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive ***,one of the main challenges is to effectively extract complementary features from different modalities for action *** this work,a novel multimodal supervised learning framework based on convolution neural networks(Conv Nets)is proposed to facilitate extracting the compensation features from different modalities for human action *** on information aggregation mechanism and deep Conv Nets,our recognition framework represents spatial-temporal information from the base modalities by a designed frame difference aggregation spatial-temporal module(FDA-STM),that the networks bridges information from skeleton data through a multimodal supervised compensation block(SCB)to supervise the extraction of compensation *** evaluate the proposed recognition framework on three human action datasets,including NTU RGB+D 60,NTU RGB+D 120,and *** results demonstrate that our model with FDA-STM and SCB achieves the state-of-the-art recognition performance on three benchmark datasets.

关键词： action recognition segment frame difference aggregation supervised compensation learning ConvNets

来源：评论

学校读者我要写书评

暂无评论

Automated Heart Disease Diagnosis and Monitoring System Using Similarity-Navigated Graph Neural Networks with Leopard Seal Optimization in IoT Healthcare Applications 4

Automated Heart Disease Diagnosis and Monitoring System Usin...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Raja, V. Sripathi Rawat, Ruchira Pandit, Karuna Dhumpati, Raghu Vekariya, Vipul Vijitha, S. B V Raju Institute of Technology Department of Biomedical Engineering Telangana Narsapur502313 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Department of Information Science and Engineering Nitte Karkala Karnataka Udupi District India Bahrain Polytechnic Isa Town Department of Computer Science and Engineering Isa Town3339 Bahrain Parul Institute of Engineering and Technology Parul University Department of Computer Science and Engineering Post Limda Gujarat Waghodia391760 India Vels Institute of Science Technology and Advanced Studies Department of computer science and Engineering Pallavaram Tamil Nadu Chennai600043 India

ISBN: (纸本)9798331540364

One of the leading causes of death worldwide continues to be heart disease;therefore, early detection and precise diagnosis are essential to better patient outcomes. The conventional methods of diagnosing chemotherapy-induced nail changes involve a great deal of laboratory testing, which is more than exhaustive. In order to tackle these obstacles, this research introduces a novel methodology for the automated diagnosis and continuous tracking of heart diseases in the IoT -based health care system, integrated with deep learning algorithms. The proposed system includes several state-of-the art techniques to improve diagnostic reliability and speed. First of all, min-max normalization is used as a pre-processing technique that aims at pre-scaling the data of patients to a consistent level and, as a result, enhancing the performance of the model. The Mud Ring Algorithm is then used for feature selection, whereby the best features are chosen together with the reduction in dimensionality to decrease computational intensity, thus improving diagnostic accuracy. The core diagnostic engine is based on Similarity Navigated Graph Neural Networks (SNGNN) and has been enhanced with Leopard Seal Optimization (LSO), a new meta-method motivated by the hunting patterns of leopard seals. This combination enables the system to relate various features and give the correct prognosis for heart diseases. These techniques, applied within the IoT framework, enable real-time monitoring and diagnosis and therefore have the benefit of being a scalable solution for modern health care systems. The results show that the proposed method for providing diagnosis of heart disease is accurate, timely, and reliable and thus has the potential to revolutionize patient management in healthcare based on the IoT. © 2024 IEEE.

关键词： Chemotherapy

来源：评论

学校读者我要写书评

暂无评论

Enhanced Privacy-Preserving WiFi Fingerprint Localization from CL Encryption

引用

Chinese Journal of Electronics 2024年第6期33卷 1435-1446页

作者： Zhiwei WANG Qiuchi ZHU Zhenqi ZHANG School of Computer Nanjing University of Posts and Telecommunications State Key Laboratory of Public Big Data Guizhou University Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu University of Information Engineering Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University

The WiFi fingerprint-based localization method is considered one of the most popular techniques for indoor localization. In INFOCOM'14, Li et al. proposed a wireless fidelity(WiFi) fingerprint localization system based on Paillier encryption, which is claimed to protect both client C 's location privacy and service provider S's database privacy. However, Yang et al. presented a practical data privacy attack in INFOCOM'18, which allows a polynomial time attacker to obtain S's database. We propose a novel WiFi fingerprint localization system based on CastagnosLaguillaumie(CL) encryption, which has a trustless setup and is efficient due to the excellent properties of CL encryption. To prevent Yang et al.'s attack, the system requires that S selects only the locations from its database that can receive the nonzero signals from all the available access points in C 's nonzero fingerprint in order to determine C's location. Security analysis shows that our scheme is secure under Li et al.'s threat model. Furthermore, to enhance the security level of privacy-preserving WiFi fingerprint localization scheme based on CL encryption, we propose a secure and efficient zero-knowledge proof protocol for the discrete logarithm relations in C's encrypted localization queries.

关键词： Location awareness Threat modeling Data privacy Protocols Databases Fingerprint recognition Trustless services Encryption Servers Wireless fidelity

来源：评论

学校读者我要写书评

暂无评论

MEVTR: A Multilingual Model Enhanced With Visual Text Representations 30

MEVTR: A Multilingual Model Enhanced With Visual Text Repres...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Xiaohua Fei, Wenlong Hu, Min Zhang, Qingyu Zhu, Aoqiang School of Computer Science and Information Engineering HeFei University of Technology China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine China

ISBN: (纸本)9782493814104

The goal of multilingual modelling is to generate multilingual text representations for various downstream tasks in different languages. However, some state-of-the-art pre-trained multilingual models perform poorly on many low-resource languages due to the lack of representation space and model capacity. To alleviate this issue, we propose a Multilingual model Enhanced with Visual Text Representations (MEVTR), which complements textual representations and extends the multilingual representation space with visual text representations. First, the visual encoder focuses on the glyphs and structure of the text to obtain visual text representations, and the textual encoder obtains textual representations. Then, multilingual representations are enhanced by aligning and fusing visual text representations and textual representations. Moreover, we propose similarity constraint, a self-supervised task to prompt the visual encoder to focus on more additional information. Prefix alignment and multi-head bilinear module are designed to acquire an improved integration effect of visual text representations and textual representations. Experimental results indicate that MEVTR benefits from visual text representations and achieves significant performance gains in downstream tasks. In particular, in the zero-shot cross-lingual transfer task, MEVTR achieves results that outperform the state-of-the-art adapter-based framework without the target language adapter. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning 42

Adaptive Configuration for Heterogeneous Participants in Dec...

引用

42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Liao, Yunming Xu, Yang Xu, Hongli Wang, Lun Qian, Chen University of Science and Technology of China School of Computer Science and Technology China University of Science and Technology of China Suzhou Institute for Advanced Study China University of California Jack Baskin School of Engineering Department of Computer Science and Engineering Santa Cru United States

ISBN: (纸本)9798350334142

Data generated at the network edge can be processed locally by leveraging the paradigm of edge computing (EC). Aided by EC, decentralized federated learning (DFL), which overcomes the single-point-of-failure problem in the parameter server (PS) based federated learning, is becoming a practical and popular approach for machine learning over distributed data. However, DFL faces two critical challenges, i.e., system heterogeneity and statistical heterogeneity introduced by edge devices. To ensure fast convergence with the existence of slow edge devices, we present an efficient DFL method, termed FedHP, which integrates adaptive control of both local updating frequency and network topology to better support the heterogeneous participants. We establish a theoretical relationship between local updating frequency and network topology regarding model training performance and obtain a convergence upper bound. Upon this, we propose an optimization algorithm, that adaptively determines local updating frequencies and constructs the network topology, so as to speed up convergence and improve the model accuracy. Evaluation results show that the proposed FedHP can reduce the completion time by about 51% and improve model accuracy by at least 5% in heterogeneous scenarios, compared with the baselines. © 2023 IEEE.

关键词： Edge computing

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：