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检索条件"任意字段=4th International Conference on Computer Vision, Pattern Recognition and Image Processing"

共 5158 条记录，以下是31-40 订阅

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Comparison of EfficientNet and VGGNet Using RGB Photos for Human Action recognition 4

Comparison of EfficientNet and VGGNet Using RGB Photos for H...

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4th international Signal processing, Communications and Engineering Management conference, ISPCEM 2024

作者： An, Ran Beijing - Dublin International College Beijing University of Technology Beijing China

ISBN: (纸本)9798331528676

In the field of computer vision, human action recognition, is a key technology, underpinning numerous application scenarios such as video surveillance, human-computer interaction, sports analysis, and more. Convolutional Neural Network (CNN)-based models have demonstrated impressive performance in human action detection difficulties due to the swift advancement of deep learning techniques. the subject matter focuses on the research of human action identification using two advanced CNN models, VGGNet and EfficientNet, on RGB image datasets. It also compares the differences in feature extraction and classification capabilities between the VGGNet and EfficientNet models. this paper selects an RGB image dataset containing information on 15 categories of human actions as the experimental basis, providing strong support for model training. During the evaluation phase, accuracy is adopted as the metric, and each model's capabilities undergo evaluation. the results indicate that the EfficientNet model exhibits higher accuracy and better generalization capabilities in human action recognition tasks, primarily due to its efficient network structure and optimized model design. the categorization of various postures aids in the advancement of technology for recognizing human behavior and helps to highlight the diversity and complexity of human behavior. ©2024 IEEE.

关键词： Convolutional neural networks

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computer vision based home automation 4th

Computer vision based home automation

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4th Annual international conference on Data Science, Machine Learning and Blockchain Technology, AICDMB 2023

作者： Srinivasan, M. Srividya, R. Rekha, N. Department of ECE KSIT Bengaluru India Department of ISE CMR Institute of Technology Bengaluru India

ISBN: (纸本)9781032426853

computer vision gives us the ability to detect and analyze human actions from images and videos. Artificial Intelligence combined with computer vision can be used to perform certain tasks based on the information detected from a video or an image. this paper introduces a home automation framework using image processing and computer vision. the work done will derive meaningful gestures of a person from a video and use it to control the home appliances. Based on the hand gesture detected, the corresponding appliance can be controlled or automated. the proposed works focuses on developing a framework in which the appliances can be automated based on desired parameters by the user. © 2024 the Author(s).

关键词： computer vision

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Research on image recognition System Based on computer Artificial Intelligence Technology 4

Research on Image Recognition System Based on Computer Artif...

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4th IEEE international conference on Power, Electronics and computer Applications, ICPECA 2024

作者： Xu, Zhihua School of Design and Art Jingdezhen Ceramic University Jingdezhen China

ISBN: (纸本)9798350359589

this paper uses mobile network mode to develop and model Python crawler based on Ubuntu16.04 and CUDA9.0. the visualization of this pattern was achieved using Tensor Board software. the hardware design of the system consists of three modules: linear array CCD sensor, DSP processor and signal processing circuit. through the reconstruction and learning of such models, the trained models are stored, so as to obtain higher precision image recognition. A method of classifying objects using Fourier description operators is proposed. the experimental results show that the accuracy of the image is 96.8% and the recognition time is 0.55 seconds. Motion tracking is based on the positioning and capture of the specific position of the human hand in each screen, and the captured frame rate is 28 frames per second. the system can quickly acquire images of 1024∗1500 pixels at a rate of 5 photos/second. through the static identification of posture and tracking of motion trajectory, the interaction between human and machine is better. © 2024 IEEE.

关键词： artificial intelligence digital signal processing fourier image identification technology mobile network

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Research on Oracle Bone Inscription Segmentation and recognition Model Based on Deep Learning 4

Research on Oracle Bone Inscription Segmentation and Recogni...

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4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Li, Donghao Du, Binfang Shandong University Qingdao China

ISBN: (纸本)9798350361643

In this paper, the automatic segmentation and recognition of oracle bone inscription images are studied. the Oracle bone inscription image segmentation model and Oracle bone inscription text recognition model are established by using computer vision technology and deep learning framework, and the application potential and scientific value of deep learning in the field of complex text image recognition are demonstrated. Firstly, we use a variety of digital image processing methods such as bilateral filtering technology and contrast-limited adaptive histogram equalization technology to optimize the recognition conditions of oracle bone inscription images. Secondly, we use the advanced Yolov8 to build a detection model to improve the text detection accuracy in oracle bone inscription images. the effect of the model was evaluated from different dimensions, such as accuracy rate, recall rate, F1 value, etc., to verify the performance of the model. Finally, we trained a model based on Resnet18 architecture to recognize the single word of the oracle bone inscription original topology image. the recognition results were displayed in the form of statistics and graphics, and the prediction accuracy of each character and the overall performance evaluation of the model were recorded in detail, thus verifying the effectiveness and practicability of the proposed method. © 2024 IEEE.

关键词： image enhancement

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Tackling "leaky" facial and object recognition operations over federated learning 4

Tackling "leaky" facial and object recognition operations ov...

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4th IEEE Interdisciplinary conference on Electrics and computer (INTCEC)

作者： Vyas, Hemendra Torrens, Paul M. NYU Comp Sci & Engn Tandon Sch Engn New York NY 10012 USA

ISBN: (纸本)9798350349467;9798350349450

Federated learning, which decentralizes learning algorithms and data over highly dynamic network and context parameters, presents significant opportunities for computing. Federated learning with facial and object recognition is of particular interest because they are converging on applications with potential privacy risks and vulnerabilities. In this paper, we examine the usage of Internet of things (IoT) for facial and object recognition;specifically, federated video sensing in monitoring and surveillance. We propose an AI-based approach for federated learning at the edge. Our proposed solution does not transmit any captured data: all personal identifying images and videos are discarded from the IoT device after processing. We suggest that key motifs from the data can instead be framed by AI and traded through the federated learning architecture without added exposure to risk of leak and without saliency loss.

关键词： federated learning computer vision AI IoT security privacy image recognition unidentified object identification

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Research on the algorithm of image processing and target detection based on embedded vision module 4

Research on the algorithm of image processing and target det...

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4th international conference on Optics and image processing, ICOIP 2024

作者： Junjie, Wu Liantao, Ding Sihan, Liu Shuai, Ren Tong, Wu College of Communication Engineering Jilin University Chang Chun China School of Mechanical and Aerospace Engineering Jilin University Chang Chun China First Automotive Work Shop -VOLKSWAGEN Automobile Company Limited Chang Chun China

ISBN: (纸本)9781510682481

To improve the recognition accuracy of the embedded visual module and make it competent for visual tasks on complex occasions, an image preprocessing method used on the OpenMV is proposed. Aiming at the two main recognition tasks of machine vision, color recognition and shape recognition, an image preprocessing algorithm and a filtering algorithm based on the OpenMV of embedded vision module are proposed for use by analyzing the interference existing in practical problems. For color features, the processing of binary segmentation and image morphology can filter the background and the noise similar to the target, which greatly improves the recognition accuracy with only a small increase in recognition time. For shape features, kernel filtering and Hough Transform are used to filter the irrelevant targets in the image, which improves the recognition accuracy, reduces the image complexity, and speeds up the operation speed of Hough Transform. the experimental and practical results show that the image preprocessing method combined with OpenMV can not only take into account the advantages of the embedded visual module but also complete the task of target recognition with high accuracy, which helps meet the needs of practical engineering and promote the wide application of embedded vision. © 2024 SPIE.

关键词： Machine vision

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8th National conference on computer vision, pattern recognition, image processing, and Graphics, NCVPRIPG 2023

8th National Conference on Computer Vision, Pattern Recognit...

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8th National conference on computer vision, pattern recognition, image processing, and Graphics, NCVPRIPG 2023

ISBN: (纸本)9789819752119

the proceedings contain 18 papers. the special focus in this conference is on computer vision, pattern recognition, image processing, and Graphics. the topics include: RGB to Chlorophyll Fluorescence image Reconstruction of Maize for Plant Phenotyping;novel Unsupervised Disease Segmentation Framework Based on Clustering;YOLOv5-MasselNet: In-Field Maize Tassel Detection and Density Estimation Using YOLOv5;MuSiC V1.0: A Software Solution for Automated Mustard Silique Count Using YOLOv5;taPaSe: Tanjore Paddy Seed Dataset;processing 3D Point Clouds for High-throughput Plant Phenotyping;a Deep Learning-Driven Contactless Finger recognition System;deep Features for Contactless Fingerprint Presentation Attack Detection: Can they Be Generalized?;unlocking Communication: Exploring Hand Gesture-Based Interaction in a Code-Mixed Conversational Speech-to-Indian-Sign-Language Translator;a Touchless Palm-Photo recognition System for Mobile and Handheld Devices;detection of Palmprint from Contactless Smartphone-Based Video Hand Dataset;improved Localization of Knuckle Regions for Contactless Acquisition;NCVPRIPG 2023 Summer Challenge on Writer Verification;C4MTS: Challenge on Categorizing Missing Traffic Signs from Contextual Cues;dePondFi’23 Challenge Summary;a Challenge on 3D Reconstruction and Restoration of Indian Heritage from Partial and Noisy Scans.

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Gate gap detection method based on double checkerboard calibration 4

Gate gap detection method based on double checkerboard calib...

引用

4th international conference on computer vision and pattern Analysis, ICCPA 2024

作者： Yang, Quanlin Huang, Xiaoliang Ren, Dexin Zhu, Xiaolong Yangtze River Three Gorges Navigation Administration Bureau Hubei Yichang China

ISBN: (纸本)9781510682528

the stable closure of the gate affects the safety performance and normal operation of the gate, and it is necessary to detect the gap distance of the closed door, but the direct observation of the gate monitoring image by the naked eye alone cannot achieve high precision and long-term accuracy. In view of the shortcomings of the existing technology, this paper proposes a gate gap detection method based on double checkerboard calibration, which can accurately detect the distance between the two gates and improve the detection accuracy. Compared with traditional methods, the method in this paper can reduce the dependence on gate and camera installation positions, thereby reducing maintenance costs. © 2024 SPIE.

关键词： Cameras Calibration image processing Imaging systems Detection and tracking algorithms Distortion image segmentation Zoom lenses Camera calibration Feature extraction

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Design of Multi View Natural Language Query System on Machine vision 4

Design of Multi View Natural Language Query System on Machin...

引用

4th IEEE international conference on Power, Electronics and computer Applications, ICPECA 2024

作者： Fang, Quanrong Investment Co. Ltd Beijing China

ISBN: (纸本)9798350359589

In various fields such as medical imaging, object detection, and video surveillance, multi view natural language query systems utilize image data to provide a more comprehensive perspective, allowing users to intuitively query and obtain information. Due to the lack of a deep understanding of natural language in the hard coded matching rule method, the query results do not match the user's intentions and are difficult to meet practical application needs. therefore, this article introduces machine vision algorithms for optimization and improvement. this article first discusses the system architecture of four modules: data input and preprocessing, visual feature extraction, natural language understanding and matching, and result generation and feedback. then, the application of machine vision technology in the system was analyzed using two calculation formulas: grayscale conversion and binarization, and natural language processing technology was briefly discussed. Subsequently, a context understanding module was added to construct a multi view natural language query system based on machine vision. Finally, two sets of simulation experiments were conducted to draw the following conclusion: compared with traditional methods, the overall average improvement in image recognition accuracy indicators is about 14.3%, while the overall average improvement in response speed indicators is about 26.5%. this research system can effectively process images from different perspectives and match them with natural language queries. © 2024 IEEE.

关键词： machine vision technology multi view processing natural language query system design

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Exploring the Capability of NASNet Model for Plant Classification on GRASP-125 Dataset 4

Exploring the Capability of NASNet Model for Plant Classific...

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4th international conference for Emerging Technology, INCET 2023

作者： Pushpa, B.R. Hemanth Kumar, M. Shobha Rani, N. Mysuru Campus Amrita Vishwa Vidyapeetham Dept. of Computer Science School of Computing India

ISBN: (纸本)9798350335750

Plant classification and identification, which has strong ties to both computer science and taxonomy, is becoming an increasingly dynamic area of research within the field of computer recognition. Researchers have utilized different techniques including image processing, pattern recognition, and machine learning to develop systems capable of accurately identifying and classifying plants. Access to large image databases and advances in image processing and artificial intelligence have led to the development of highly accurate plant identification systems. these systems have the potential to greatly reduce the amount of time and proficiency required for plant identification, which are only achievable by skilled taxonomists. In this study, we experimented with the Greek vAScular Plants (GRASP) dataset, consisting of images across 125 different plant species native to the mountains belonging Oiti and Parnassus in central Greece, to perform automatic plant identification using a deep learning approach namely NASNet. these plant species, which include both rare and aesthetically pleasing varieties, are often found along popular hiking routes in the region. Our method for plant classification utilizes deep learning techniques on the GRASP-125 dataset, with the goal of improving the accuracy and efficiency of plant identification. © 2023 IEEE.

关键词： computer vision

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