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检索条件"任意字段=3rd International Conference on Image Processing and Vision Engineering, IMPROVE 2023"

共 1700 条记录，以下是151-160 订阅

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Overview of image segmentation methods based on deep learning 3

Overview of image segmentation methods based on deep learnin...

引用

3rd international conference on Electronic Information engineering and Data processing, EIEDP 2024

作者： Wang, Yiwen Department of Software Engineering and Intelligent Technology Tianjin University of Finance and Economics Tianjin300222 China

ISBN: (纸本)9781510680531

image segmentation is an important branch of computer vision, which has been widely used in many research fields. In order to understand the research status in the field of image segmentation, this paper systematically analyses and compares the traditional image segmentation method and the image segmentation method based on deep learning. Firstly, the development, advantages, and disadvantages of traditional image segmentation methods are summarized according to the three types of segmentation methods based on threshold, edge, and region. Then, the segmentation network models of three commonly used image segmentation methods based on deep learning, namely, fully convolutional neural network, pyramid scene analysis network, and Mask R-CNN, are analyzed. Based on the previous experimental results and the current research progress based on deep learning models, the problems of contour edge optimization and multi-level pixel information fusion in the field of image segmentation are summarized. At the same time, improvement ideas are put forward for the existing problems. Finally, the improvement and development of future image segmentation methods are prospected, which provides a reference for the subsequent research of segmentation methods. © 2024 SPIE.

关键词： image segmentation

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Intelligent Control System of Construction Machinery Based on PLC and Machine vision 3

Intelligent Control System of Construction Machinery Based o...

引用

3rd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2023

作者： Zhua, Jinfeng Guob, Lina Sunc, Liwen Shandong Institute Commerce and Technology Applied Electronics Department Jinan250103 China

ISBN: (纸本)9781665472784

In the field of industrial automation, the application of machine vision(MV) technology in industrial production positioning detection is developing rapidly, and the positioning task can still be accomplished by image detection and recognition in the harsh environment of industrial sites. And construction machinery(CM) also towards the direction of intelligence and automation, people also pay more and more attention to the design of CM control system(CS) research. This paper develops an intelligent CS for CM suitable for industrial production process. The system processes the image information by MV system, and then the processed data is calculated by PLC, which combines MV technology and PLC technology to realize the detection of pulse signal frequency and the monitoring of CM and equipment status. The test results of the intelligent CS module in this paper also show that the system meets the design requirements and can be put into engineering production applications. © 2023 IEEE.

关键词： Control systems

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Apply Deep Learning-based CNN and LSTM for Visual image Caption Generator 3

Apply Deep Learning-based CNN and LSTM for Visual Image Capt...

引用

3rd international conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Indumathi, N. Divyalakshmi, R.J. Stalin, J. Ramachandran, V. Rajaram, P. Srm Institute of Science and Technology Computer Science and Applications Chennai India Sethu Institute of Technology Computer Science and Business Systems Virudhunagar India Computer Science and Engineering Gitam School of Computing Bengaluru India

ISBN: (纸本)9798350399264

Implemented image captioning is becoming a need. Deep neural network models enable integrated applications to generate and caption images. image captioning describes an image. It requires identifying an image's main objects, properties, and relationships. It produces correct sentences. The creation of image caption generators, which examine the content of an image and offer pertinent descriptions, makes use of deep learning and computer vision techniques. One element of this method involves classifying objects in the image using English keywords derived from training datasets. The caption generator was created by combining LSTM and CNN. In this paper, we propose a deep-learning model that uses computer vision and machine translation to characterize images and generate captions. The model successfully recognizes and labels visual items and their relationships. Transfer Learning will be used to demonstrate the suggested experiment, coupled with the Flickr8k dataset and the Python3 programming language. This study will also look into the functions and construction of neural networks. The proposed model achieves a BELU Score of 69.8. © 2023 IEEE.

关键词： Long short-term memory

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A Lung Cancer Tumor image Segmentation Method of A CFC-MSPCNN based on PET/CT 3

A Lung Cancer Tumor Image Segmentation Method of A CFC-MSPCN...

引用

3rd international conference on Computer vision and Pattern Analysis, ICCPA 2023

作者： Lian, Jing Yang, Xuefeng Niu, Xiaojiao Cao, Yuzhu Lanzhou Jiaotong University School of Electronic and Information Engineering No. 88 West Anning Road Gansu Lanzhou China

ISBN: (纸本)9781510667563

To address the problems of low segmentation accuracy and machine complexness of ancient pulse coupled neural network (PCNN) in medical image process, a Converged-FCMSPCNN (CFC-MSPCNN) model is projected. Compared with earlier PCNN models, this model additionally optimizes and enhances the synaptic weight matrix, link strength and dynamic threshold, simplifies the parameter settings and reduces the quantity of iterations. In addition, we add a balance parameter Q to regulate the dynamic threshold to improve the model's control over neuronal image processing. Through relevant experiments, we demonstrate that our algorithm has higher results compared with alternative algorithms to accurately section carcinoma lots and considerably reduces the randomness and unpredictability of firing neurons. © 2023 SPIE.

关键词： image segmentation

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image Captioning based on Encoder Decoder Architecture 3

Image Captioning based on Encoder Decoder Architecture

引用

3rd IEEE international conference on Intelligent Techniques in Control, Optimization and Signal processing, INCOS 2024

作者： Saranya, M. Veera Anusuya, V. National Engineering College Department of Computer Science and Engineering Kovilpatti India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361186

images are essential for communicating ideas, feelings, and narratives in the era of digital media and content consumption. Computers to produce textual data for an image that replaces humans. image captioning is a fascinating fusion of computer vision (CV) and Natural Language processing (NLP) that aims to generate text from an image. By using these technologies, images can be used as an approachable, meaningful, and descriptive form of communication. Because of its wide range of uses, image captioning has attracted a lot of attention. Strong feature representations and context-aware language generation algorithms are necessary to overcome the major challenge of bridging the semantic gap between visuals and text. In this research work, EfficientNetV2B0 is utilized in the encoder part, for extracting objects from an image. Then Long Short-Term Memory (LSTM), a type of recurrent neural network as a decoder for generating descriptions by using encoder output. The suggested approach yields superior results than the earlier research when compared to the current method on the measures of Bilingual Evaluation Understanding and Consensus Based image Description Evaluation scores. © 2024 IEEE.

关键词： Long short-term memory

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A Survey on Crime Detection using CCTV Systems 3

A Survey on Crime Detection using CCTV Systems

引用

3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Sheela, A Jeba Balaji, S. Balaji, B. Hemanth Kumar, U. Easwari Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343632

In order to improve security measures across numerous domains, such as public safety, transportation, and critical infrastructure protection, the use of closed-circuit television (CCTV) systems for threat analysis has become increasingly important. The technical abstract gives a summary of the most recent algorithms and techniques used in threat analysis when using CCTV. This study emphasizes the importance of spatial and temporal reasoning, machine learning models like Support Vector Machines (SVM), Haar-Cascade, ViF (Violent Flows), OViF (Oriented Violent Flows), RINOC (Real-time image and Video Object Classification), and LRT (Live-Streaming Real-Time). Insights into the diverse methodologies that can be applied to enhance the effectiveness of CCTV-based threat analysis, the efficiency of CCTV systems and their impact on detecting and reducing criminal activities are discussed. The comparative outcomes of different detection approaches and their ensembles have been empirically discussed. © 2023 IEEE.

关键词： CCTV (Closed Circuit Television) CNN Deep learning Haar-Cascades image Classification image processing SVM (Support Vector Machine)

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image-Based Length and Width Measurement of Crimped Tension Clamp 3

Image-Based Length and Width Measurement of Crimped Tension ...

引用

3rd international conference on Intelligent Power and Systems, ICIPS 2023

作者： Shao, Huitu Lv, Jiliang Qu, Shengguan Ceng, Zhengfeng School of Mechanical and Automotive Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350328691

Associated to the crimp quality, the crimping length and width are important parameters in the crimping process. An innovative image-based parameter measurement method was proposed. Firstly, the original image was preprocessed using adaptive cropping, CLAHE enhancement, and Otsu thresholding. Then edges were obtained through morphological processing and fitted using Random Sampling Consensus (RANSAC). Finally, the crimping length and width were measured by image analysis technique. The experiment results show that the proposed measurement method has advantages of high efficiency, high accuracy and good repeatability. ©2023 IEEE.

关键词： image enhancement

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image vision-Based Pull-Up Recognition 3

Image Vision-Based Pull-Up Recognition

引用

3rd international conference on Electronic Information engineering and Computer Science, EIECS 2023

作者： Ke, Mingyan Tang, Haoran Zhu, Huanan Li, Mo Beijing University of Information Science and Technology Changping Beijing China

ISBN: (纸本)9798350316674

With the accelerated pace of modern life and increased work pressure, people tend to live in an extremely depressing and lack of exercise environment, and diseases and various physical health conditions come one after another. Therefore, this project team plans to use the Kinect sensor launched by Microsoft to achieve the pull-up test automatically, and apply it to the general public. This project is based on image vision to identify and analyse pull-ups, using Kinect V2 to interact with LabVIEW, and extracting and identifying human bones through Kinect and analysing the data information. When LabVIEW receives the coordinate data of each bone point of the user, it uses the coordinate height comparison between the head and the crossbar and the size of the bending degree of the arm to judge the counting. And levels have been added so that users get a workout while experiencing the fun of getting through the levels. © 2023 IEEE.

关键词： Kinect V2 LabVIEW pull-up recognition skeleton recognition

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Research of Digital image processing Technology of Photoelectric Theodolite's Target Based on MATLAB 3

Research of Digital Image Processing Technology of Photoelec...

引用

3rd IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2023

作者： Li, Ke Zhao, Lijian Xu, Ruxiang Zhou, Haiyuan Liu, Xinming Qian, Fanyuan Sun, Xiaodong Marine Department of Satellite Tracing and Metering Jiangyin China

ISBN: (纸本)9781665472784

Digital image processing is a technique to digitized image data,which is also called computer image processing. Modern technology keeps digital image processing evolving and expands the application scope. Because of the complexity of the sea scene, as well as the the characteristics of the photoelectric theodolite, the background of uneven homogeneity can be occured in the measured images over the time, and various kinds of clouds and other complex backgrounds may appear a because of the changing weather. How to suppress the diverse backgrounds, enhance the contrast and improve the target extraction ability are the key to successfully capturing the tracking target. This paper takes the processing operation of edge detection and pseudo-color processing. Meanwhile, an improved K-means clustering method is proposed;different kinds of clusters were selected for different kinds of images and realized the rapid and effective image segmentation. The clear edge and detail of image can be realized after the abovementioned operations. In this paper, the processing algorithm of the theodolite image has advantages and disadvantages,the corresponding algorithm can be taken according to specific requirements in practical application, which can be technical reference for the image target recognition and feature extraction. © 2023 IEEE.

关键词： K-means clustering

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Research on detection of safety helmet wearing based on improved YOLOv4 3

Research on detection of safety helmet wearing based on impr...

引用

3rd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Wang, Jie Xue, Jing Huang, Peng Tianjin University of Technology Tianjin China Northwest Agriculture & Forestry University Xi'an China Tianjin China

ISBN: (纸本)9798350398410

With the development of China's infrastructure construction and the rapid expansion of new infrastructure, the volume of engineering construction is increasing, and the safety management of personnel during the construction process has become the key to ensure the smooth implementation of the project. In this paper, we propose an improved YOLOv4 helmet wearing detection algorithm. The algorithm combines BN layer and convolutional layer to reduce the computation of modified network forward inference, uses K-means clustering algorithm to improve the prior frame dimension, uses flexible NMS algorithm for confidence weight modification to solve the label rewriting problem, and applies multi-scale feature fusion to improve the model recognition accuracy. The results show that the improved model is 3.4 times faster than YOLOv4 and can be used for real-time detection of whether construction workers are wearing helmets under different construction site conditions, which is conducive to improving safety inspection and supervision. The application of vision technology and computer image technology has achieved the purpose of enhancing the safety and security of construction personnel through the means of information management. © 2023 IEEE.

关键词： image enhancement

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