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检索条件"任意字段=4th International Conference on Intelligent Systems and Pattern Recognition-ISPR"

共 1872 条记录，以下是11-20 订阅

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Accelerating Traditional Object Detection Methods on Sophisticated Embedded systems 4th

Accelerating Traditional Object Detection Methods on Sophist...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Sehairi, Kamal Bouhafs, Abdelkader Boucherit, Ibtissam Mama Bouwmans, thierry Chouireb, Fatima Ecole Normale Super Laghouat Dept Phys Lab Appl Sci & Didact Laghouat Algeria Univ Amar Telidji Laghouat Dept Elect Telecommun Signals & Syst Lab Laghouat Algeria Univ La Rochelle Dept Comp Sci Lab Math Image & Applicat La Rochelle France

ISBN: (纸本)9783031821523;9783031821530

Identifying and locating objects in images and videos, including elements like traffic signs, vehicles, buildings, and people, constitutes a fundamental and demanding task in computer vision, known as object detection. Due to the higher computing complexity of this technique and the large amount of data carried by the video signal, it is nearly impossible for ordinary general-purpose processors GPPs or CPUs to run these techniques in real-time, especially for embedded systems applications. therefore, special hardware that can acquire, control, or execute in parallel is required. these specialized hardware systems include Digital Signal Processors DSPs, Field Programmable Gate Arrays FPGAs, Visual Processing Units VPUs, Tensor Processing Units TPUs, Neural Processing Units NPUs or Graphics Processing Units GPUs. this work presents the benefits of accelerating traditional object detection methods on a high-end embedded system, the Jetson Nano Developer Kit. this single computer board is equipped with the Tegra K1 System on Chip SoC, which is composed of a quad-core ARM A15 and 192 cores of Kepler-embedded GPU. Computing acceleration was ensured via the use of the CUDA OpenCV library for both the Histogram of Oriented Gradients HOG and the Haar Cascade Classifier. For VGA resolution, results reveal that the GPU implementation on this embedded system is 1.4x faster than the CPU for the HOG method and 2x for the Haar Cascade Classifier method.

关键词： Object detection Machine Learning Haar Cascade HOG Local feature descriptors GPU implementation OpenCV CUDA SoC Tegra X1 Jetson Nano

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Efficiency Meets Resilience: Accelerating Object Detection in Embedded Environments through Compressive Sensing 4th

Efficiency Meets Resilience: Accelerating Object Detection i...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Bouderbal, Imene Amamra, Abdenour Ecole Natl Preparatoire Etud Ingn Badji Mokhtar Rouiba BP 05 Algiers Algeria Ecole Mil Polytech Bordj El Bahri BP 17 Algiers Algeria

ISBN: (纸本)9783031821554;9783031821561

Optimizing convolutional neural networks (CNNs) for real-time performance in resource-constrained settings remains a challenge. this study introduces a novel approach to CNN design, integrating compressive sensing (CS) techniques to enhance both efficiency and robustness. Our proposed CS-based CNN architecture facilitates real-time object detection in embedded environments by significantly reducing computational complexity and improving transmission efficiency. Specifically, the CS paradigm is employed as a sampling-reconstruction network within the detection CNN, resulting in streamlined processing and reduced model complexity. Previous research demonstrated a remarkable 57% reduction in floating-point operations per second (FLOPs) and a 30% increase in speed for the redesigned SSD model compared to its original counterpart [4]. In this study, we extend our investigation to assess the resiliency of the CS-based CNN architecture against adversarial perturbations. Utilizing different augmented test sets, we evaluate the performance of the CS-based model alongside its traditional baseline. Our findings reveal that the CS-based CNN exhibits superior resilience, with a smaller decline in mean average precision (mAP) under adversarial conditions: a drop of 29.1% for the CS-based model compared to a 50.8% drop for the original architecture, for the worst-case scenario. these results underscore the potential of CS-based CNNs to enable efficient and robust real-time computer vision applications in embedded environments.

关键词： Convolutional Neural Networks Compressive Sensing Real-time Performance Robustness Adversarial attacks Embedded systems Object Detection

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MCDPS: Enhancing Clinical Decision Support for Multiple Chronic Disease Prediction systems Using Ensemble Machine Learning Approaches 4th

MCDPS: Enhancing Clinical Decision Support for Multiple Chro...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Kumar, Kanak Verma, Anshul Verma, Pradeepika Banaras Hindu Univ Dept Comp Sci Varanasi 221005 Uttar Pradesh India Indian Inst Technol Technol Innovat Hub Patna 801103 Bihar India

ISBN: (纸本)9783031821554;9783031821561

People today suffer from various chronic diseases due to lifestyle choices and environmental conditions. Early prediction of these diseases is crucial to prevent them from worsening. However, it is often challenging for physicians to accurately diagnose these issues independently. A computational model based on big data analytics has numerous applications in the medical field. Advancements in machine learning (ML) and information technology have enabled more accurate recognition of diseases, health emergencies, and conditions. the advent of predictive algorithms has transformed disease diagnosis in the medical field. Previously, patient data records were meticulously examined to predict diseases and develop advanced models for trend analysis. However, with the rise of data analytics-driven intelligence, the evaluation of disease symptoms has become more accurate and efficient. these technologies enable the creation of predictive models capable of analyzing vast amounts of patient data to identify hidden patterns, aiding in early disease detection and diagnosis. this study explores the development of an ensemble ML-based multiple chronic disease prediction system (MCDPS) focused on three major diseases: chronic kidney disease (CKD), liver disease, and heart disease. the system utilizes ensemble ML models, including Decision Tree (DT), Gradient Boosting Classifier (GBC), Extreme Gradient Boosting (XGBoost), and Extra-Trees classifiers (ETC), to predict diseases. Its user-friendly and straightforward design makes it accessible to beginners. the system's performance in predicting the three chronic diseases has been evaluated and compared with other traditional models. the results show that the DT algorithm achieved an accuracy of 99%, 85%, and 83% for predicting CKD, heart disease, and liver disease, respectively.

关键词： Multiple Chronic Disease Prediction System Machine Learning Decision Tree Gradient Boosting Classifier Extreme Gradient Boosting Extra-Trees classifiers

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intelligent customer service system of subway based on semantic decision-making judgment 4

Intelligent customer service system of subway based on seman...

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4th international conference on Machine Learning and intelligent systems Engineering (MLISE)

作者： Liu, Xinyu Shanghai Univ Engn Sci Sch Urban Railway Transportat Shanghai Peoples R China

ISBN: (纸本)9798350375084;9798350375077

this study introduces an intelligent customer service system for urban rail transit, addressing inefficiencies and high labor costs in existing systems' problem classification and feedback mechanisms. Leveraging semantic understanding, the system integrates advanced speech recognition, intention classification, and entity extraction to automate the processing and intelligent classification of passenger hotline calls. Post-evaluation, the system demonstrated a minimum of 4.55% enhancement in data processing accuracy and F1 score, respectively, validating its efficacy in enhancing efficiency and precision. Furthermore, the research delves into the practical application of entity recognition, offering insights into the integration of natural language processing in intelligent customer service systems.

关键词： natural language processing semantic recognition text classification entity recognition

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Multimodal Facial recognition Based Attendance Monitoring System 4

Multimodal Facial Recognition Based Attendance Monitoring Sy...

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4th international conference on Ubiquitous Computing and intelligent Information systems, ICUIS 2024

作者： Harini, H. Shreya, C. Shivani, B. Tejaswini, P.U. Patil, Amarnath Bangalore India

ISBN: (纸本)9798331529635

this research study focuses on developing an automated attendance system using facial recognition technology. the system utilizes the Local Binary patterns (LBP) algorithm to accurately recognize student faces. By replacing traditional manual attendance methods, this system aims to improve efficiency, accuracy, and reduce the time required for attendance marking. the system automates the face recognition process, eliminating the need for manual verification and reducing the potential for human error. this research contributes to enhancing the efficiency and effectiveness of educational administration. © 2024 IEEE.

关键词： Local binary pattern

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Speech recognition for intelligent System in Service Robots: A Review 4

Speech Recognition for Intelligent System in Service Robots:...

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4th international conference on Electrical Engineering and Computer Science, ICECOS 2024

作者： Atika, Ratna Dwijayanti, Suci Yudho Suprapto, Bhakti Doctoral Program in Engineering Science Universitas Sriwijaya Department of Electrical Engineering Polytechnic of Sriwijaya Palembang Indonesia Faculty of Engineering Universitas Sriwijaya Department of Electrical Engineering Palembang Indonesia Faculty of Engineering Palembang Universitas Department of Electrical Engineering Sriwijaya Indonesia

ISBN: (纸本)9798350368253

Speech recognition and response system technology in service robot research continues to evolve alongside technical advances and the increasing demand for intelligent automation across industries. the development of machine learning, digital signal processing, and artificial neural networks has brought significant advancements to speech recognition systems. While speech recognition has been implemented in various systems, there is limited discussion on categorizing these systems by examining four aspects: speech recognition applications, datasets used, emotional speech recognition, and automatic speech recognition. In this study, a review of these four aspects is conducted, focusing on the algorithms and methods used, along with their advantages and disadvantages, particularly in the context of implementing them in service robots using the Indonesian language. this study involves a literature review of 100 research papers from the last five years. the review concludes that the use of the transformer method combined with other techniques and Indonesian language datasets is still very limited. therefore, future research will focus on developing and implementing these methods in humanoid service robots. © 2024 IEEE.

关键词： intelligent systems

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Research on operation and maintenance practice of intelligent facilities based on visual recognition technology 4

Research on operation and maintenance practice of intelligen...

引用

4th international conference on Computer Vision and pattern Analysis, ICCPA 2024

作者： Tuerhong, Miralimujiang Guo, Xinying Aizaizi, Guzainuer Pan, Xudong Bolati, Yedeli State Grid Xinjiang Electric Power Co. Ltd. Information and Communication Co. Urumqi Xinjiang830000 China

ISBN: (纸本)9781510682528

With the continuous development of artificial intelligence technology, intelligent facility operation and maintenance practice based on visual recognition technology has become one of the research hotspots. Based on the background of intelligent facility operation and maintenance, this study discusses the application of visual recognition technology in facility operation and maintenance. Firstly, through the analysis of the current situation of intelligent facility operation and maintenance, the requirements and challenges based on visual recognition technology are put forward. Secondly, combined with deep learning and image recognition technology, a set of intelligent facility operation and maintenance system is designed, and the practical application and verification are carried out. Finally, through the analysis and summary of the experimental results, the validity and feasibility of the intelligent facility operation and maintenance practice based on visual recognition technology are verified, which provides a useful reference for the research and practice of intelligent facility operation and maintenance field. © 2024 SPIE.

关键词： Scheduled maintenance

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Computer Vision-Based Hand Gesture recognition 4

Computer Vision-Based Hand Gesture Recognition

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4th international conference on Ubiquitous Computing and intelligent Information systems, ICUIS 2024

作者： Swedheetha, C. Naveen, Palanichamy Akilan, T. Manikandan, P. Pushpavanam, B. Velammal College of Engineering and Technology Department of Cse Madurai India Dr. N.G.P. Institute of Technology Coimbatore India Amity University Department of Iqac Kolkata India Kalasalingam Academy of Researchh and Education Department of Ece Virudhunagar India Psna College of Engineering and Technology Department of Eee Dindigul India

ISBN: (纸本)9798331529635

Hand gesture recognition plays a vital role in bridging communication gaps for individuals with hearing impairments. this abstract explores the application of computer vision and machine learning techniques to give sign language gestures. By analyzing and classifying the intricate movements of hand and finger configurations, these systems facilitate real-time translation of sign language into text or speech. the potential impact on accessibility and inclusivity is substantial, empowering the deaf and hard-ofhearing community to communicate effortlessly with the broader society. this abstract encapsulates the significance of hand gesture recognition in breaking down linguistic barriers and fostering a more inclusive world. © 2024 IEEE.

关键词： Real time systems

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ESIC 2024 - 4th international conference on Emerging systems and intelligent Computing, Proceedings

ESIC 2024 - 4th International Conference on Emerging Systems...

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4th international conference on Emerging systems and intelligent Computing, ESIC 2024

ISBN: (纸本)9798350349856

the proceedings contain 137 papers. the topics discussed include: recognition of emotional speech using MFCC and machine learning technique;target driven autoencoder: a supervised learning approach for tumor segmentation;early detection of Parkinson’s using machine learning;predicting the stock market index using GRU for the year 2020;detection of bone fracture using deep learning;a pragmatic approach of heart and liver disease;predominant musical instrument detection using ensemble learning;skin cancer detection and classification using deep learning;air pollutant concentration analysis and prediction using ai;a comparative study of deep learning techniques for network intrusion detection;and an efficient approach for optimizing the CA selection search space in a blockchain network.

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the intelligent safety management platform of power distribution station based on system linkage is constructed 4

The intelligent safety management platform of power distribu...

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4th international conference on Electronics, Circuits and Information Engineering, ECIE 2024

作者： Dong, Haodong Shi, Guobing Li, Xian Detroit Green Technology Institute Hubei University of Technology Wuhan430068 China Huazhong Agricultural University Energy Management Center Wuhan430070 China

ISBN: (纸本)9798350388312

Ensuring safety is the top priority in the power supply process. Based on the system linkage, using face recognition technology and Internet of things technology, this paper provides an unattended safety management scheme for hydropower supply and distribution sites with active discovery, system linkage and intelligent processing based on system linkage, using face recognition technology and Internet of things technology, and integrating and optimizing video surveillance, smoke detection, data transmission and access control systems, which can actively capture abnormal situations such as intrusion, smoke and operation faults, and trigger the video alarm system to provide on-site images in time. © 2024 IEEE.

关键词： Alarm systems

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