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检索条件"任意字段=7th International Conference on Vision, Image and Signal Processing, ICVISP 2023"

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7th international conference on vision, image and signal processing, icvisp 2023

7th International Conference on Vision, Image and Signal Pro...

引用

7th international conference on vision, image and signal processing, icvisp 2023

ISBN: (纸本)9781839539848

the proceedings contain 47 papers. the topics discussed include: a modified UNet network bridged with multiscale context fusion for photovoltaic panel image segmentation;a new method for radar emitter individual identification based on VMD and multi-image feature combination;research on axle bearing fault detection method based on multilayer feature fusion under sparse training samples;diffusion posterior sampling for remote sensing image fusion;mutual reconstruction-based linear discriminant hashing for image retrieval;joint face super-resolution and deblurring using multi-task feature fusion network;AmpNorm: an effective style normalization method for single domain generalization;construction of marine target detection dataset and target detection methods;and deep learning sea surface object detection method based on infrared image.

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Research on Visual Target Detection and Recognition of Shopping Robots Based on Improved YOLO Algorithm 7th

Research on Visual Target Detection and Recognition of Shopp...

引用

7th international conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Lu, Yufan Zhejiang Gongshang University Hangzhou China

ISBN: (纸本)9789819624089

this research aims to improve the visual target detection and recognition capabilities of shopping robots in various sales environments by optimizing and improving the YOLO algorithm, in order to improve accuracy and real-time performance. the research method involves embedded spatial hierarchical sampling technology and it adapts to image processing of different sizes, uses a separate convolutional neural network structure to reduce computational complexity, and cultivates a more concise network model by refining the effective data of complex models. Experimental results show that the improved YOLO algorithm performs well in weak Its average accuracy has been significantly improved under light, medium light and strong light environments, especially in the detection of small items. A study shows that improved programming significantly improved the vision of shopping assistance robots. Recognition capabilities enable robots to provide more accurate and faster services in real shopping environments. © the Author(s) 2025.

关键词： Machine vision

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Fault Detection Method of Electrical Wiring Based on Computer vision 7

Fault Detection Method of Electrical Wiring Based on Compute...

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7th international conference on vision, image and signal processing, icvisp 2023

作者： Gao, Hongyan Institute of Railway Locomotive and Rolling Stock Wuhan Railway Vocational College of Technology Hubei Wuhan China

ISBN: (纸本)9781839539848

In order to solve the problem of low efficiency of wiring error detection in the process of batch manufacturing of electrical cabinet, a new method of automatic wiring error detection using computer vision technology was studied and introduced. Based on the improvement of Canny operator, the adaptive smooth filter and morphological closure operator are used to filter the image to remove noise, the maximum inter-class variance matrix is used to adaptively select the threshold value, reconstruct the image model, improve the image edge detection accuracy, accurately determine the position and number of wires in the electrical cabinet, and finally compare with the data in the corresponding junction box. To determine whether the wiring is correct. the experimental results show that the proposed method has a high recognition accuracy in complex environment. the location data and the corresponding wire number are consistent with the template information in the database, and the average accuracy is up to 92.2%. Using this method can well solve the need of wiring testing in the production of electronic products, and can effectively improve the quality of products and production efficiency. © the Institution of Engineering & Technology 2023.

关键词： Computer vision

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Efficient feature matching algorithms applied to robust image processing 7

Efficient feature matching algorithms applied to robust imag...

引用

7th international conference on Intelligent Computing and signal processing, ICSP 2022

作者： Chen, Kaige Ye, Ning Xie, Jianhong Taiyuan University of Technology School of Mechanical and Transportation Engineering Taiyuan China Dalian Polytechnic University School of Art and Design Liaoning Dalian China Shenyang University of Technology School of Artificial Intelligence Liaoning Shenyang China

ISBN: (纸本)9781665478571

image feature matching is an essential problem in computer vision. Also, feature matching is an important task in many computer vision applications, such as in VR technology, drones, and autonomous driving. In this paper, four algorithms for matching are presented first. We perform outdoor scene feature matching experiments on four algorithms: Surf, Sift, Orb, Brisk. the original image is rotated, the sharpness is continuously blurred, the scene is transformed, specific regions are scaled, and the resolution is changed. the number of feature points that correctly matched the transformed image to the original image was compared. In this paper, the stability is determined by comparing the operation time of the four algorithms in the case of unified processing. then, the RANSAC algorithm detects the proportion of internal and external points and compares the robustness. It is concluded that the ORB algorithm is the fastest, and the SURF algorithm is the most robust. © 2022 IEEE.

关键词： Computer vision

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Multi-scale Information Fidelity Approach for Full Reference image Quality Assessment

Multi-scale Information Fidelity Approach for Full Reference...

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7th IEEE international conference on Wireless Communications and signal processing (WCSP)

作者： Feng, Mingkun Zhao, Shengmei Cui, Jingwu Nanjing Univ Posts & Telecommun Inst Signal Proc & Transmiss Nanjing Jiangsu Peoples R China Zhejiang Univ Sci & Technol Sch Informat & Elect Engn Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781467376877

the Information Fidelity Criterion (IFC) of image assessment metric is based on the statistical mutual information shared by reference image and distorted image. IFC is parameterless and superior to traditional methods. However, human vision system (HVS) is adaptive to different scale feature of image. A multi-scale IFC approach to model the characteristics of HVS was proposed in this paper, in which image was locally filtered by Gaussian dynamic windows ratio to different scales. Finally, assessment scores for different scales were pooled with weight of contrast sensitivity function. Experimental results showed that the performance of the proposed approach was superior to other methods.

关键词： computer vision image quality assessment multi-scale information fidelity

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Evaluating stereo cartoon depth maps as scene information for the blind

Evaluating stereo cartoon depth maps as scene information fo...

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7th IASTED international conference on signal and image processing

作者： Picton, P Capp, M Univ Coll Northampton Sch Appl Sci Northampton NN2 6JD England

ISBN: (纸本)0889865167

Important scene information may be relayed to a blind person via mobility aids that incorporate an image to sound mapping. However, these devices are frequently both tiring and stressful to use. A new display technique, which combines a stereo edge depth map with a cartoon-like scene representation is described. Experimental results are included that demonstrate the effectiveness of the algorithm.

关键词： real-time vision stereoscopic vision navigation aids

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NRNet: Retinex Decomposition with Realistic Noise 7

NRNet: Retinex Decomposition with Realistic Noise

引用

7th international conference on Intelligent Computing and signal processing, ICSP 2022

作者： Song, Liye Yang, Jindan Li, Li Peng, Jishen Liaoning Technical University Faculty of Electrical and Control Engineering Huludao China

ISBN: (纸本)9781665478571

Computer vision tasks fail in low-light environments, so high-quality restoration of low-light images is of great significance to improve the robustness of computer vision. Traditional low-light enhancement algorithms use statistical methods or need to manually adjust parameters, which will fail in poor enhancement effect and robustness. Based on the deep learning method and the Retinex method, this paper proposes a self-supervised low-light enhancement algorithm based on the attention mechanism. We decouple the illumination component and reflection component of Retinex, and then synthesize it into an input RGB image, and finally use the estimated components to adaptively adjust different areas of the image. In experiments, we use several different datasets to test our method. Experiments show that our method is able to enhance low-light images under various scene conditions. © 2022 IEEE.

关键词： Computer vision

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Fault detection method of electrical wiring based on computer vision

Fault detection method of electrical wiring based on compute...

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7th international conference on vision, image and signal processing (icvisp 2023)

作者： H. Gao Institute of Railway Locomotive and Rolling Stock Wuhan Railway Vocational College of Technology Wuhan Hubei People's Republic of China

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the vision-based metric self-localization of indoor mobile robot using projective geometry

The vision-based metric self-localization of indoor mobile r...

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7th international conference on signal processing

作者： Fang, Q Xie, CX S China Univ Technol Dept Mech Engn Guangzhou 510640 Peoples R China

ISBN: (纸本)7121002159

this paper addresses the vision-based self-localization of an indoor service robot worked with a single vehicular camera. Based on the principle of projective geometry and the extended virtual image plane, the transverse position and orientation of robot is calculated through considering the image plane and floor plane as a whole. the longitudinal position is acquired by using the monocular stereovision method based on distance constraint along feature points of nature or artificial landmark. After a simple off-fine process about landmark, the service robot can work well in a building. the validity and feasibility of the approach have been demonstrated through experiments.

关键词： indoor service robot self-localization projective geometry monocular stereovision

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YOLOX-Nano: Intelligent and efficient dish recognition system 7

YOLOX-Nano: Intelligent and efficient dish recognition syste...

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7th international conference on Intelligent Computing and signal processing, ICSP 2022

作者： Zhong, Liangtang Tan, Hao Liao, Jinrui Guangdong Ocean University College of Mathematics and Computer Science Zhanjiang China

ISBN: (纸本)9781665478571

In order to realize the application of image recognition technology in dish recognition, this paper takes dishes in university cantons as samples, uses dish data to train YOLOX-Nano Model, uses ncnn computing framework to deploy the trained model on Android platform, and uses camera to take photos to identify dishes. After the test, in the canteen, restaurant and other complex environment, the program runs stably, can quickly and accurately identify dishes image. the results show that the trained model is lightweight, stable and efficient, and can meet the expected design requirements. © 2022 IEEE.

关键词： Computer vision

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