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检索条件"任意字段=3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023"

共 459 条记录，以下是21-30 订阅

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MRI-Based Brain Tumour Detection and Classification Using Random Forest Algorithm 3rd

MRI-Based Brain Tumour Detection and Classification Using Ra...

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3rd international conference on Intelligent Systems and Sustainable Computing, ICISSC 2023

作者： Jareena Begum, D. Chokkalingam, S.P. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9789819783540

A brain tumour develops when cells in the brain multiply abnormally and out of control. The possibility of fatality makes this growth dangerous. The brain regulates everything from memory to vision to emotions. Recognizing these tumours is a challenging and complex task due to their location, size, and shape. There have been a number of successful attempts to enhance detection. However, the current level of precision is insufficient. This study details a method with a high likelihood of success in identifying brain cancers. The approach is implemented in Python LAB by use of an image segmentation technique and a classifier. One such classifier is the Random Forest Algorithm. The Principal Component analysis (PCA) and the Discrete Wavelet Transform (DWT) are also employed. The created method is put to the test using a dataset available on the Kaggle platform. The acquired results were approximately 97.68% accurate. A confusion matrix and a comparison of the developed method to other research in the literature are included in the investigation to facilitate the implementation of the proposed strategy in image testing. This Research shows that the offered system is superior to others in terms of detection rate, false positive rate, and recall. Results from this study showed that the developed method was effective at detecting brain tumours due to its high levels of accuracy, precision, and recall. According to the proposed strategy, it is essential to provide professionals who diagnose brain tumours with access to such technology. © The Author(s) 2025.

关键词： Image segmentation

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Real-Time Insights and Dynamic Performance Visualizations for Unprecedented Impact in Ball Badminton 3rd

Real-Time Insights and Dynamic Performance Visualizations fo...

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3rd international conference on Sports Engineering, ICSE 2023

作者： Rohith Gowda, M. Pai, Aditi N. Vishwanatha, C.N. Akash, M.P. Ranganath, G.H. Bhaskar, H.N. Department of Computer Science and Engineering R. V. College of Engineering Bengaluru India Department of Physical Education and Sports R. V. College of Engineering Bengaluru India Department of Physical Education and Sports SJB Institute of Technology Bengaluru India Department of Physical Education and Sports SBRRMFGC Mysuru India

ISBN: (纸本)9789819782963

The absence of advanced analytical tools has been a major obstacle in the world of ball badminton, a traditional sport. The lack of real-time data and valuable insights has long impeded players, coaches, and spectators. This paper introduces an innovative system aimed at transforming the ball badminton experience, enhancing player performance, engaging spectators, and providing valuable tools for coaches and fans through real-time insights and dynamic performance visualizations. This approach involves developing a system, preferably an application, to track the movement of the player and measure position, acceleration, and speed using computer vision and predicting tactics to assist during training, tracking the short trajectory of the ball to assist during practices for improvement, displaying live statistics such as player stats (points won, errors, aces), match progress (scoreboard), and historical data (head-to-head records) to provide context and analysis during the match, besides assisting the umpire in making decisions. Benefits to the viewers are the display of real-time statistics, fan engagement through quizzes on the sport, and result prediction. Coaches can use it to make strategic decisions, players to review their performance, and fans to gain deeper insights into the match. Additionally, it employs a markerless motion capture system, which relies on deep learning for human position estimation and computer vision techniques. To transform pixel data into court coordinates and enable the measurement of parameters like distance covered, court positioning, and average player speeds for ball badminton players, the methodology relies on the inverse perspective mapping method. One of the algorithms applied in this context is the Lucas-Kanade optical flow algorithm, which aids in player tracking and position estimation, contributing to the overall effectiveness of the technology. The technology will track player movements and tactical insights with great preci

关键词： Deep learning

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Ultra Energy Efficient Reliable and Robust DLJLFET-Based-PUF for IoT Devices 3rd

Ultra Energy Efficient Reliable and Robust DLJLFET-Based-PUF...

引用

3rd international conference on Machine vision and Augmented Intelligence, MAI 2023

作者： Rajan, Chithraja Kumar, Rakesh Panchore, Meena Singh, Jawar School of Computer Science and Engineering Ramdeobaba University Maharashtra Nagpur440013 India Department of Electronics and Communication Engineering National Institute of Technology Patna Bihar800005 India Department of Electronics and Communication Engineering Indian Institute of Technology Patna Patna India

ISBN: (纸本)9789819743582

Physically Unclonable Function (PUF) emerged as a prominent hardware security solution for Internet of Things (IoTs) devices. PUFs are also used for generating secret keys for cryptography and for low-cost authentication in the high security of integrated circuits (ICs). Some natural variations occur during the manufacture of ICs. These variations are inevitable and uncertain. The PUF generates a different and unique random number by using this variation as the output key for the same input, even though this variation in the output is very small. In this article, a detailed comparative performance analysis of junctionless field effect transistor (JLFET)-based PUF and dopingless JLFET (DLJLFET)-based PUF is presented. A PUF circuit is designed using a five-stage ring oscillator (RO). It is observed that the delay in DLJLFET-based RO is 61% lower and consumes 47% less energy than JFLET-based RO at a supply voltage of 0.5 V because JLFET shows a higher leakage current due to high doping in the channel. Further, we did Monte Carlo simulation for 100 runs and observed that DLJLFET-PUF gives more unique PUF as mean HD is close to 50% and frequency of oscillation of DLJLFET is about 2 times higher than JLFET-PUF so DLJLFET-PUF will take less time during encryption and decryption for incoming and outgoing data, thus the output key generation will be faster. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Hardware security

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Contour Detection of Seeds Based on Traditional and Convolutional Neural Network (CNN) Based Algorithms 28th

Contour Detection of Seeds Based on Traditional and Convolut...

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28th international conference on Image Processing, computer vision, and pattern Recognition, IPCV 2024, and 23rd international conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in computer Science, computer Engineering and Applied Computing, CSCE 2024

作者： Zhao, Kai Neilsen, Mitchell L. Department of Computer Science Kansas State University ManhattanKS66505 United States

ISBN: (纸本)9783031859328

computer vision algorithms are becoming more widely used in the agricultural domain. Edge detection algorithms are used to detect plant or seed contours. These contours identify regions of interest and delimit the size of plants or seeds from a single perspective. By combining contours from different angles, other plant phenotypes, such as volume, can be computed. This paper delves into the potential of edge detection, specifically contour detection, in the domain of seed phenotyping. Contour detection is significantly influenced by image quality, with color saturation due to ambient light and background color playing important roles. This paper expands traditional contour detection algorithms to address their limitations and improve their accuracy. Images are captured using different physical characteristics and image backgrounds. A consistent background color allows for more contrast with the seeds being analyzed. This paper compares various traditional detection methods with convolutional neural network (CNN) detection methods. The analysis aims to highlight the strengths and weaknesses of each technique, offering valuable insights for seed researchers because contour detection is essential in supporting non-destructive measurement of seed volume. This volume can be used to compute the density of irregularly-shaped seeds. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Application of a semantic segmentation method based on deep learning in unity scene construction 3

Application of a semantic segmentation method based on deep ...

引用

3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Qi, Jiangyuan Li, Hui School of Art and Design Changjiang Polytechnic China School of Computer Science Wuhan Donghu University China

ISBN: (纸本)9781510667563

This paper proposes the application of deep learning-based semantic segmentation in Unity scene construction as a means to enhance efficiency and quality. By automatically recognizing and segmenting various objects in an image, this method enables developers to rapidly generate 3D models and textures for the scene. The study showcases the effectiveness of the proposed technique in reducing the time and effort required for scene construction through experiments conducted within Unity. © 2023 SPIE.

关键词： Semantic Segmentation

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Research on Daily Behavior Recognition Method Based on computer vision 3

Research on Daily Behavior Recognition Method Based on Compu...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Wan, Jiao Li, Kai Hu, Meihui Yang, Dawei Cao, Jinping Information and Communication Company of State Grid Xinjiang Electric Power Co Ltd Xinjiang Urumqi830000 China

ISBN: (纸本)9781510667563

With the continuous development of science and technology in China, the popularity of computers has brought a great impact on people's production and life. And all walks of life have also been continuously studying computer vision technology, and in continuous practice, it has been applied to multiple fields, such as industrial and agricultural production, human-computer interaction, social public security, virtual reality, and so on, making people's lives enter a new form. This study mainly analyzes the advantages of the application of computer vision based human behavior recognition and specific human behavior recognition methods. © 2023 SPIE.

关键词： computer vision

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Study on extraction of key features of sugar orange phenotype 3

Study on extraction of key features of sugar orange phenotyp...

引用

3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Wang, Shilong Zhu, Jinghuan Guangxi Science & Technology Normal University Guangxi Laibin546199 China

ISBN: (纸本)9781510667563

Efficient and accurate segmentation of the basic features in the image of sugar orange is the primary work for intelligent classification of sugar orange. In order to achieve the purpose of grading according to the key quality characteristics of sugar orange, the peel region, fruit stalk region and peduncle region were segmented respectively, and the basic feature information of each region was extracted. Firstly, the background of the feature image was segmented, and then the fruit diameter, shape, ripeness, texture, color distribution and other features were extracted for grading. © 2023 SPIE.

关键词： computer vision

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analysis of Machine vision-based Defect Detection for Logistics Conveyor Belts 3

Analysis of Machine Vision-based Defect Detection for Logist...

引用

3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Xie, Mengfan Qingdao Engineering Vocational College Qingdao266000 China

ISBN: (纸本)9781510667563

The logistics industry is an important pillar of national economic development. In the logistics and warehousing industry, conveyor belts are one of the important equipment for transporting goods. However, long-term operation can easily lead to various types of defects such as belt breakage, cracking, and wear, which seriously affect logistics operations. Therefore, this paper proposes a defect detection solution for logistics conveyor belts based on machine vision technology. By using machine vision technology to filter, segment, and edge detect images, the corresponding feature parameters are extracted and input into a BP neural network for learning, so as to identify different types of defects. This study uses this solution to process and analyze the surface images of conveyor belts samples through machine vision technology, which can accurately identify different types of defects and their locations, achieving automated defect detection of conveyor belt surfaces and improving logistics operation efficiency and safety. © 2023 SPIE.

关键词： computer vision

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Aesthetic Evaluation of Handwritten Chinese Characters Based on Deep Learning 3

Aesthetic Evaluation of Handwritten Chinese Characters Based...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Zhou, Biliang Chen, Zhuo School of Computer Science Hubei University of Technology Hubei Wuhan430068 China

ISBN: (纸本)9781510667563

The aesthetic evaluation of handwritten Chinese characters has important due value in primary and secondary education. This paper proposes to use deep learning to solve this problem. Firstly, using the public handwritten Chinese character aesthetic scoring dataset, training is carried out in various deep learning network models, and finally the network model with better scoring effect is determined. The experimental results show that the deep learning network model used in this paper has an accuracy rate as high as 83% in the aesthetic evaluation of Chinese characters, and the error performance is better than that of human evaluation. © 2023 SPIE.

关键词： Deep learning

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Method of feature extraction and recognition for surface defect of sugar orange 3

Method of feature extraction and recognition for surface def...

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3rd international conference on computer vision and pattern analysis, iccpa 2023

作者： Wang, Shilong Zhu, Jinghuan Liu, Yuxue Guangxi Science & Technology Normal University Guangxi Laibin546199 China

ISBN: (纸本)9781510667563

The surface integrity, rot degree, mechanical damage, rupture, scar and other states of sand sugar orange fruit can be reflected from the surface defects of sand sugar orange. The surface defects of sand sugar orange can be used as an important characteristic parameter to judge the surface integrity, rot degree, mechanical damage, rupture, scar of sand sugar orange fruit. By segmenting the background of the collected feature image, the surface defects of the fruit peel were detected, the common surface defects of the orange were identified, and whether the orange was ruptured or scarred was judged, and the classification was realized. © 2023 SPIE.

关键词： computer vision

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