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检索条件"任意字段=11th International Conference on Computer Technologies and Development, TechDev 2022"

共 1567 条记录，以下是61-70 订阅

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ROBUST GRAPH DICTIONARY LEARNING 11

ROBUST GRAPH DICTIONARY LEARNING

引用

11th international conference on Learning Representations, ICLR 2023

作者： Liu, Weijie Xie, Jiahao Zhang, Chao Yamada, Makoto Zheng, Nenggan Qian, Hui Qiushi Academy for Advanced Studies Zhejiang University China College of Computer Science and Technology Zhejiang University China Okinawa Institute of Science and Technology Japan Kyoto University Japan RIKEN AIP Japan Zhejiang Lab China State Key Lab of CAD&CG Zhejiang University China Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies China Advanced Technology Institute Zhejiang University China

Traditional Dictionary Learning (DL) aims to approximate data vectors as sparse linear combinations of basis elements (atoms) and is widely used in machine learning, computer vision, and signal processing. To extend DL to graphs, Vincent-Cuaz et al. 2021 proposed a method, called GDL, which describes the topology of each graph with a pairwise relation matrix (PRM) and compares PRMs via the Gromov-Wasserstein Discrepancy (GWD). However, the lack of robustness often excludes GDL from a variety of real-world applications since GWD is sensitive to the structural noise in graphs. this paper proposes an improved graph dictionary learning algorithm based on a robust Gromov-Wasserstein discrepancy (RGWD) which has theoretically sound properties and an efficient numerical scheme. Based on such a discrepancy, our dictionary learning algorithm can learn atoms from noisy graph data. Experimental results demonstrate that our algorithm achieves good performance on both simulated and real-world datasets. © 2023 11th international conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Signal processing

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Retrainable Hand Gesture Recognition Model Driven by Edge AI 11

Retrainable Hand Gesture Recognition Model Driven by Edge AI

引用

11th international conference on Dependable Systems and their Applications, DSA 2024

作者： Hsu, Tse-Chuan Chang, Dong-Meau Soochow University Department of Computer Science & Information Management Taipei Taiwan Lingnan Normal University School of Computer Science and Intelligence Education China

ISBN: (纸本)9798331532390

Based on computer vision and machine learning, accurate hand behavior and gesture recognition are crucial, especially for missing or incomplete hand models. Finger joint point prediction technology is of great value for applications such as virtual reality and human posture recognition. However, hand joint point prediction models, such as Google's MediaPipe, perform well in full-finger models but are ineffective in missing-finger situations. Missing fingers are familiar in clinical medicine, rehabilitation facilities, and unique scenarios such as hand injuries or congenital hand deformities. Accurate prediction of hand joints is critical for hand rehabilitation, prosthetic design, and human motion analysis and inspires the development of related technologies. Since traditional prediction models rely on complete hand data, and missing fingers can make the hand structure irregular, the complexity of prediction increases. this study proposes an improved prediction model focusing on hand joint point prediction in the case of missing fingers, hoping to improve prediction accuracy and provide valuable reference for future applications and research. Among the research results, we successfully integrated the new training image model with MediaPipe, significantly improving missing fingers' prediction accuracy. © 2024 IEEE.

关键词： Prediction models

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Building Trust: IoT Security and Blockchain Integration 18

Building Trust: IoT Security and Blockchain Integration

引用

18th INDIAcom;11th international conference on Computing for Sustainable Global development, INDIACom 2024

作者： Reegu, Faheem Ahmad Ayoub, Shahnawaz Dar, Arshad Ahmad Hussain, Gousiya Gulzar, Yonis Fatima, Ummatul Jazan University College of Computer Science and Information Technology Saudi Arabia Glocal University Glocal School of Science and Technology Mirzapur India Mewar University Department of Computer Sciences Chittorgarh India King Faisal University College of Business Administration Department of Management Information Systems Saudi Arabia Aligarh Muslim University Faculty of Science Department of Statistics and Operations Research Aligarh India

ISBN: (纸本)9789380544519

Blockchain technology has captured considerable attention in recent years due to its unique potential to reshape the financial industry. this innovative breakthrough is increasingly gaining prominence, especially within finance, where it has demonstrated efficacy in streamlining processes and addressing cost concerns. It simplifies the authentication and tracking of intricate, multi-step actions requiring verification and traceability. Furthermore, blockchain finds applications in managing voting platforms, designations, and activities, offering a reliable means of validating official assertions. the Internet of things (IoT) represents a significant paradigm shift, integrating millions and billions of smart devices endowed with processing, sensing, and actuation capabilities. the convergence of IoT with social networking principles has spawned the concept of Social IoT, reflecting the societal integration of these technologies. While IoT primarily revolves around connecting various smart gadgets, its infrastructure remains vulnerable to security and privacy threats due to the lack of foundational security measures. this study endeavors to delve into the challenges inherent in IoT and investigate how these obstacles can be mitigated through the integration of blockchain technology. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Attacks blockchain Data Sharing Internet of things Security

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Proceedings - 11th IEEE international conference on Intelligent Computing and Information Systems, ICICIS 2023

Proceedings - 11th IEEE International Conference on Intellig...

引用

11th IEEE international conference on Intelligent Computing and Information Systems, ICICIS 2023

ISBN: (纸本)9798350322101

the proceedings contain 85 papers. the topics discussed include: traditional and deep learning techniques in image steganography: recent advances;deep learning for extracting human movement patterns from spatio-temporal data;speech emotion recognition: enhancing human-computer interaction;a combined ELM and CNN model architecture for accurate viral family DNA classification;ML driven priority-based constrained routing for pollution management in ITS;on development of computer aided system for detecting brain neurological disorders;CalorieMe: an image-based calorie estimator system;deepfake detection using EfficientNet and XceptionNet;dental disease detection based on CNN for panoramic dental radiographs;and AI-based detection of myocardial infarction through electrocardiogram signals: a review.

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A GPS-based Face Attendance Register System using Android Applications stored in the Cloud 18

A GPS-based Face Attendance Register System using Android Ap...

引用

18th INDIAcom;11th international conference on Computing for Sustainable Global development, INDIACom 2024

作者： Murali, N. Rajesh, R. Sridharan, S. Mariadas, A. Emmanuel Peo Murugan, S. Palani Manikandan, S. E.G.S. Pillay Engineering College Department of Department of Computer Science and Engineering Tamil Nadu Nagapattinam India E.G.S. Pillay Engineering College Department of Computer Science and Engineering Tamil Nadu Nagapattinam India University College of Engineering Department of Computer Science and Engineering Tamil Nadu Thirukkuvalai India E.G.S. Pillay Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Nagapattinam India E.G.S. Pillay Engineering College Department of Information Technology Tamil Nadu Nagapattinam India

ISBN: (纸本)9789380544519

the system is a face-based attendance system for students that make use of multi-CNN (Convolutional Neural Network) technology with GPS tracking. the device simplifies the process of taking attendance for both teachers and students while offering precise and effective attendance monitoring. the method makes use of GPS tracking to pinpoint the location of student and get confirmation of their attendance. the multi CNN technology is utilized to improve the attendance's accuracy. Tracking multiple CNN models are combined in the multi-CNN system to increase the process's accuracy for tracking attendance. Additionally, the system makes use of facial recognition technologies to make sure. the appropriate pupil is noted as present. When a student leaves a class, the department head and parents are both notified at the same time. A web-based dashboard and a mobile app for students and teachers make up the system. Every database is kept in cloud storage. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： android application cloud storage Face-based attendance gps technology image recognition

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Current Situation and development of Outcome-Based Education in computer Teaching 11

Current Situation and Development of Outcome-Based Education...

引用

11th international conference on Educational and Information Technology (ICEIT)

作者： Li Gang Wang Hong Song Xinmin Shandong Normal Univ Jinan 250300 Peoples R China

ISBN: (纸本)9781665445467

In the context of new engineering, the concept of OBE (Outcome-Based Education) has begun into the curriculum construction of colleges and universities, opening a new round of teaching practice reform. In order to understand the development of OBE concept in computer specialty, explore the teaching mode of OBE and application status of OBE in computer teaching. Firstly, this paper analyses the mainstream literature of OBE in computer teaching from 2016 to 2021 by using Cite Space software, and find some important patterns. then, this paper discusses from three aspects: keywords, clustering and timeline. Finally, from the teaching objectives, the teaching method, the teaching view transformation to the computer teaching development proposed the suggestion. It also provides a reference for the application and reform of the OBE concept in teaching of other subjects.

关键词： outcome-based engineering certification the new engineering computer major knowledge graph

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Test Suite Minimization through PSO 11

Test Suite Minimization Through PSO

引用

11th international conference on Reliability, Infocom technologies and Optimization, ICRITO 2024

作者： Ahuja, Neeru Bhatia, Pradeep Kumar Guru Jambheshwar University of Science and Technology Dept. of Computer Science and Engineering Haryana Hisar125001 India

ISBN: (纸本)9798350350357

Regression testing is a critical stage that ensures the software changes are not affecting existing functionality. Ideally, conducting regression tests after each software change is essential. However, the exhaustive repetition of full tests for every alteration proves time-consuming, expensive, and demands significant resources. Test suite minimization serves as a solution by eliminating redundant test cases. this research presents an advanced approach to eliminate redundant test cases effectively. the proposed method focuses on identifying a concise yet effective set of test cases that align with requirements and efficiently uncover faults. this streamlined approach not only reduces testing expenses but also contributes to a more efficient testing process. the study demonstrates its effectiveness in minimizing the test suite by employing the Particle Swarm Optimization (PSO) algorithm with varied inertia weight strategies. Results from simulations indicate the success of this approach in reducing the test suite size while maintaining or even improving code coverage. Comparative analysis against Genetic Algorithms (GA) and Artificial Bee Colony (ABC) methods underscores the superior performance of PSO, specifically with tailored inertia weight strategies. this research significantly contributes to optimizing software testing methodologies, ultimately enhancing fault detection efficiency in software development. © 2024 IEEE.

关键词： Software testing

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development of Photovoltaic Building Integrated Auxiliary Design Platform Based on BIM System

Development of Photovoltaic Building Integrated Auxiliary De...

引用

computer technologies and development (techdev), international conference on

作者： Jing Wang China Airport Planning & Design Institute Co. Ltd. Northwest Branch Xi’an Shaanxi Province China

As a more important element in green building, Photovoltaic (PV) building not only contributes to the realization of energy saving and emission reduction, but also promotes the healthy development of the industry. therefore, this paper designs an auxiliary platform for PV building integration based on BIM system. the study uses PVsyst, a PV system design software, to clarify key parameters such as the installation and selection of inverters and PV modules, and then simulates the PV power generation. the information model of this residence is constructed using eQUEST software to analyze the building energy consumption in three aspects: PV power generation, air conditioning energy efficiency, and envelope structure. the results show that PV buildings can promote the realization of energy self-sufficiency and, combined with BIM technology, can play a role in promoting the development of green and energy-efficient buildings.

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Next-Gen Parking Facilities: Deep Learning for Face and License Plate based Access 18

Next-Gen Parking Facilities: Deep Learning for Face and Lice...

引用

18th INDIAcom;11th international conference on Computing for Sustainable Global development, INDIACom 2024

作者： Balasubramanian, K. Kannan, N. Sivakami, S. Senthil, S. Immaculate Rexi Jenifer, P. Murali, N. E. G. S. Pillay Engineering College Department of Computer Science and Engineering Nagapattinam India K. Ramakrishnan College of Technology Department of Computer Science and Engineering Trichy India School of Computing SASTRA Department of Computer Science and Engineering India

ISBN: (纸本)9789380544519

Parking congestion has become a major problem in today's metropolitan environments, resulting in lost time, higher emissions, and irritated drivers. there is a severe shortage of parking places in metropolitan areas because of the ever-growing number of the vehicles and the ever-growing urban population. this shortage has exacerbated traffic congestion and environmental pollution in addition to making it difficult and time-consuming to find a parking space. Conventional parking management systems are finding it harder and harder to handle these issues;they frequently depend on physical barriers or manual ticketing. Innovative approaches that incorporate automation and technology are becoming more prevalent to address this problem. Conventional parking management systems frequently depend on human intervention and physical infrastructure, which leads to inefficiencies and constrained scalability. In contrast, new opportunities for a more intelligent, effective, and user-friendly experience are made possible by the incorporation of deep learning methods and cutting-edge computer vision technology into parking management. this system makes use of two essential elements: automatically recognizing license plate numbers for vehicle identification and facial recognition technology for person identification. through the smooth integration of these technologies, the system not only makes parking easier, but it also improves security and maximizes parking space usage. We will examine the essential elements, advantages, and possible effects of the Face and Number Plate-Based Smart Parking System in this survey. According to experimental findings, employing a face- and number-plate verification method can increase the efficiency of smart parking systems. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Deep learning Face recognition system Features based matching Slot allocation Smart parking system

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A YOLO-Based Framework for Accurate Identification of Wheat Mosaic Virus Disease 11

A YOLO-Based Framework for Accurate Identification of Wheat ...

引用

11th international conference on Reliability, Infocom technologies and Optimization, ICRITO 2024

作者： Sharma, Jeeya Kumar, Deepak Chattopadhay, Saumitra Kukreja, Vinay Verma, Aditya Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun India

ISBN: (纸本)9798350350357

the serious threat Wheat Streak Mosaic Virus (WSMV) poses to wheat production is brought to light in this study's discussion of the major issue of WSMV detection in Indian wheat crops. Crop quality is severely affected by WSMV, which can be transmitted by the Wheat Curl Mite (WCM). WSMV is an RNA virus that is monopartite in structure and belongs to the Tritimovirus genus. When wheat leaves are infected with WSMV, a unique yellow mosaic pattern and slow development are observed. the disease was first identified in Nebraska in 1922. WCMs contribute to the virus's spread over the disease cycle as they act as carriers. Our research employs Deep Learning Models (DL) and the YOLO (You Only Look Once) method to tackle this issue in a novel way. the use of YOLO requires enhancing the accuracy and efficiency of detection by recognizing complex WSMV patterns. With the use of this YOLO model, the research can get 97.56% precision for wheat mosaic virus recognition. It is possible to detect diseases earlier and create specific action plans for their management with the help of this integration of DL models. By using modern methods for precise and effective WSMV detection, this research offers an important stage in safeguarding wheat output. © 2024 IEEE.

关键词： Crops

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