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检索条件"任意字段=International Conference of Soft Computing and Pattern Recognition"

共 7529 条记录，以下是81-90 订阅

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The technique of parsing vehicle wiring harness tooling diagram based on pattern recognition 3

The technique of parsing vehicle wiring harness tooling diag...

引用

3rd international conference on High Performance computing and Communication Engineering, HPCCE 2023

作者： Guo, Zhibo Jiang, Wei Song, Yanhai Sun, Chenglin Wang, Nan Qiao, Xiaoli Changchun University of Science and Technology Changchun China Changchun CRRC Railway Vehicles Co. Ltd. Changchun China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

This paper analyzes the main elements of vehicle wire harness diagrams and summarizes the rules that a correct wire harness diagram should adhere to. Building upon this foundation, with the aid of Teigha, successful extraction of entities within vehicle wire harness diagrams has been achieved. Node recognition Algorithm and Wire harness recognition algorithm have been designed, which can correctly analyze elements in the harness diagram and extract data from them. A comparative experiment was conducted with the traditional electronic wiring board, and the experimental results showed that the intelligent electronic wiring board using the algorithm shortened the average path resolution time from 4.3 hours to 7.6 seconds, and no errors occurred during the processes. © 2024 SPIE.

关键词： Vehicles

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Vehicle Theft Detection Using Neural pattern recognition 3

Vehicle Theft Detection Using Neural Pattern Recognition

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3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Jane Rubel Angelina, J. Subhashini, S.J. Kumar Rapuri, Anil Ravva, Vennela Rasala, Raghavendra Ray Adurgam, Sai Dcepak Kalasalingam Academy of Research and Education Dept of Computer Science and Engineering TamilNadu Krishnankoil India SRM Madurai College for Engineering and Technology Dept of Computer Science and Engineering TamilNadu Sivagangai India

ISBN: (纸本)9798350322842

Finding stolen cars is becoming increasingly important in many urban regions. An automated system for scanning license plates can recognize vehicle numbers without the need for human interaction. This work proposes a vehicle theft detection system based on neural pattern recognition, gaussian filter, and equilibrium optimization. The proposed architecture has significant speedup and higher accuracy rates. The proposed number plate recognition method has a maximum accuracy rate of 94% and an average reduction in the processing time of 32%. pattern recognition is the process of detecting regularities and patterns in data using machine learning. These analogies may now be uncovered via statistical analysis, historical data, or machine-generated knowledge. © 2023 IEEE.

关键词： Image segmentation

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2023 10th international conference on soft computing and Machine Intelligence, ISCMI 2023

2023 10th International Conference on Soft Computing and Mac...

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10th international conference on soft computing and Machine Intelligence, ISCMI 2023

ISBN: (纸本)9798350359374

The proceedings contain 41 papers. The topics discussed include: optimizing vehicle loan default detection with synthetic balancing techniques;LigMANet: towards designing a lightweight crowd counting model;optimization of acoustic and flow performance in a perforated muffler;complexity measurement for multitask classification problems in machine learning;prototype of a system to assist the urologist in the recognition of urinary bladder tumors in MRI images;sign language translator for dumb and deaf;didactic system for the control of bleeding;classifying DNS over HTTPS malicious/benign traffic using deep learning models;and a study on developmental artificial neural networks that integrate multiple functions using variational autoencoder.

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Complex scene fall detection method based on improved YOLOv5 24

Complex scene fall detection method based on improved YOLOv5

引用

13th international conference on computing and pattern recognition, ICCPR 2024

作者： Li, Yifan Liu, Pengyu Kong, Lili Deng, Yiyang Liu, Weilong Chen, Shanji Chen, Jiali Yuan, Bowen School of Information Science and Technology Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China Hebei Hongyi Environmental Protection Technology Co. Ltd Dingzhou Hebei China Beijing-Dublin International College at BJUT Beijing University of Technology Beijing China Information Technology Co. Ltd Dingzhou Hebei China College of Physics and Electronic Information Engineering Qinghai Minzu University Qinghai China

ISBN: (纸本)9798400717482

Aiming at the existing deep learning-based fall detection model in multiple complex scenes such as multi-person scenes, long-distance scenes, and occlusion scenes, there are problems such as leakage detection and false detection. In this paper, we take the falling person as the research object, construct a dataset containing multiple complex scenes such as multi-person scenes, long-distance scenes, and occlusion scenes, and propose a fall detection model based on improved YOLOv5. By improving the backbone network and neck network structure of the detection model, the problem of low accuracy of fall detection due to incomplete target deformation features and target detail features in complex scenes is solved. The proposed algorithm in this paper achieves an average accuracy of 92.78% for fall detection in complex scenes, and the detection speed reaches 36 frames/second. © 2024 Copyright held by the owner/author(s).

关键词： Fall detection

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An Improved soft-YOLOv5 Algorithm Applied to Computer Motherboard Defects Detection 6

An Improved SOFT-YOLOv5 Algorithm Applied to Computer Mother...

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6th IEEE international conference on pattern recognition and Artificial Intelligence, PRAI 2023

作者： Zhang, Zhen Zhou, Yujie Xie, Rule Wang, Zhen Huizhou University Openharmony Innovation Lab Huizhou China

ISBN: (纸本)9798350325485

As far as we know, computers are very mature electronic products. With time passing, most computers are assembled by the manufacturer before distribution. However, a problem occurs when people send their computers for repair. Maintainers often increase the time cost of maintenance due to some subtle components on the computer motherboard. In order to improve the efficiency of maintenance and quickly locate the place that needs to be repaired or replaced, in this paper, we improve the NMS operation in Yolov5 by using the soft-NMS algorithm, which successfully improves the performance of YOLOv5 in defect detection on computer motherboards. Compared to YOLOv5, the precision value of soft-YOLOv5 increases from 83.3% to 84.2% and the mAP@0.5 value of soft-YOLOv5 increases from 87.1% to 90.3%. Consequently, soft-YOLOv5 has better performance on computer motherboard defect detection. © 2023 IEEE.

关键词： Defects

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Optimization Study of KNN Classification Algorithm on Large-Scale Datasets: Real-Time Optimization Strategy Based on Balanced KD Tree and Multi-threaded Parallel computing 4

Optimization Study of KNN Classification Algorithm on Large-...

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4th international conference on Intelligent computing and Human-Computer Interaction, ICHCI 2023

作者： Cao, Kangjie Wu, Jinyao Huang, Qianhang Gan, Yichao Minzu University of China Department of Computer Science and Technology Beijing China

ISBN: (纸本)9798350343113

The K-Nearest Neighbors (KNN) algorithm is a classical supervised learning method widely used in classification and regression problems. However, the KNN algorithm faces serious challenges when dealing with high-dimensional large-scale datasets, mainly in terms of high computational complexity, low search efficiency, and difficulty in real time. In this study, an optimization strategy based on balanced KD tree and multithreaded parallel computing is proposed to address this problem. Experimental results show that the optimized KNN algorithm significantly improves the search speed while maintaining classification accuracy, realizes real-time classification of large-scale datasets, and provides a powerful tool for pattern recognition, data mining, and other fields in the era of big data. © 2023 IEEE.

关键词： pattern recognition

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A Hybrid Method of SVG Parameter Calibration Based on Particle Swarm Optimization and soft Actor-Critic 7

A Hybrid Method of SVG Parameter Calibration Based on Partic...

引用

7th international conference on pattern recognition and Artificial Intelligence, PRAI 2024

作者： Zhao, Ao Xiang, Xuanchen Zhao, Ligang Zhen, Hongyue Diao, Ruisheng Yan, Kaibiao Xu, Guangjun ZJU-UIUC Institute Zhejiang University Haining China Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350350890

Static var generators (SVGS) are essential for compensating reactive power and maintaining bus voltage levels before and after large disturbances. Accurate modeling of SVG controller parameters is critical to ensure the reliability of dynamic simulation in power system operation. This paper introduces a novel SVG parameter identification method, which integrates the benefits of particle swarm optimization (PSO) and reinforcement learning (RL) to improve the efficiency and accuracy of parameter calibration. We use simulation data generated by PSD BPA software combined with actual power grid data as the environment to optimize the parameter settings of SVG. This study combined PSO with the soft Actor-Critic (SAC) algorithm to optimize and calibrate these parameters. Compared with the simulation results, our method shows significant advantages in calibration accuracy and processing speed and effectively improves the simulation quality and practicability of the SVG model. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Detection of Islanding in AC Microgrid Using Random Forest And Scalogram Image Based Local Binary pattern 4

Detection of Islanding in AC Microgrid Using Random Forest A...

引用

4th international conference on Power, Control and computing Technologies, ICPC2T 2025

作者： Pal, Kumaresh Namrata, Kumari Akella, Ashok Kumar Meena, Veerpratap Padmanaban, Sanjeevikumar Department of Electrical Engineering National Institute of Technology Jamshedpur India Department of Electrical Engineering IT and Cybernetics University of South-Eastern Norway Porsgrunn Norway

ISBN: (纸本)9798331530402

Islanding is a significant obstacle along with excessive penetration of DG sources. The islanding could cause harm to the customers and their equipment. The IEEE 1547 DG interconnection regulations stipulate that the DG must be disconnected, and the islanding must be observed within two seconds. Basically, this paper presents a novel method for detecting islanding based upon image pattern recognition using random forest (RF) classification technique is proposed. Images are utilized to derive the local binary pattern (LBP) characteristics to identify non-islanding as well as islanding events. Hence, the time series signal is obtained and transformed into scalogram images at the point of common connection. These images are utilized to extract the features using LBP, which is then utilized as a feature vector input for the RF classifier for training as well as testing. It uses the total harmonics distortion (THD) characteristic of the voltage to derive scalogram image. The RF classifier's effectiveness is assessed with 5-fold cross-validations. The result from classification demonstrates that detection of islanding using RF classifier and LBP feature being used for image pattern recognition achieved excellent results with 98.89% accuracy and detection time of 158 milliseconds. © 2025 IEEE.

关键词： Local binary pattern

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pattern recognition Search: An Advancement Over Interpolation Search

Pattern Recognition Search: An Advancement Over Interpolatio...

引用

IEEE international conference on Big Data and Smart computing (BigComp)

作者： Yilmaz, Shahpar Nadeem, Yasir Mehdi, Syed Ali Jamia Hamdard New Delhi India

ISBN: (纸本)9781665421973

Interpolation Search is an algorithm that performs the task of searching for a data through a sorted array by opting a divide and conquer approach, meaning filtering out data to reduce the sample size through unique deductions. In the case of interpolation search specifically, the procedure is to assume the array to be in the form of a perfect arithmetic progression series and then predict the ideal position of the key element. This paper proposes a new searching technique which is an advancement of interpolation search, in the name of 'attern recognition Search'. We look to highlight some of the key drawbacks of interpolation search which are accounted for in the pattern recognition Search.

关键词： Sorting Time Space Complexity Array Index

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Skin texture recognition of leg images based on chaotic mapping reorganization features 3

Skin texture recognition of leg images based on chaotic mapp...

引用

3rd international conference on Intelligent computing and Human-Computer Interaction, ICHCI 2022

作者： Zhang, Tianshu Tang, Chaoying Huang, Qiaoyue Nanjing University of Aeronautics and Astronautics Automation College Nanjing China

ISBN: (纸本)9781510661301

In criminal and victim identification, when information such as fingerprint and facial images cannot be obtained, the development of other new bio-metric recognition has become an important task. It is found from investigations that the lower leg is often exposed in an evidence image. If we can use the information to identify the identity of the suspect, it will be a great break-through for criminal investigation. Unlike faces or fingerprints, the image of a lower leg does not have many discriminative features. Therefore, capturing more information from an image has become the key to the success of recognition. Despite the rapid development of deep learning in recent years and the wide application of convolutional neural networks in biometric recognition, they are very dependent on a large amount of training data. In this paper, we propose a recognition method based on the combination of chaotic mapping and local binary pattern (LBP), which captures the nonlinear features of the image. Experimental results show that the method proposed in this paper has a better recognition rate and an encouraging performance. © 2023 SPIE.

关键词： Local binary pattern

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