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检索条件"任意字段=Iranian Conference on Machine Vision and Image Processing"

共 11506 条记录，以下是351-360 订阅

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Advancing Retinal image Segmentation: A Denoising Diffusion Probabilistic Model Perspective 7

Advancing Retinal Image Segmentation: A Denoising Diffusion ...

引用

7th IEEE International conference on Multimedia Information processing and Retrieval (MIPR)

作者： Alimanov, Alnur Islam, Md Baharul Bahcesehir Univ Dept Comp Engn Istanbul Turkiye Florida Gulf Coast Univ Dept Comp & Software Engn Ft Myers FL USA

ISBN: (纸本)9798350351439;9798350351422

Retinal images and vessel trees play a crucial role in aiding ophthalmologists to identify and diagnose various illnesses related to the eyes, blood vessels, and brain. However, manual retinal image segmentation is a laborious and highly skilled procedure, posing challenges in terms of both difficulty and time consumption. This study proposes a novel approach to retinal image segmentation, leveraging the Denoising Diffusion Probabilistic Model (DDPM) for precise performance. To our best knowledge, DDPM is being applied in this domain for the first time. Our approach incorporates a novel constraint to prevent DDPM from generating vessel structures that not present in the original retinal images during the segmentation process. Additionally, our model is not limited to the original DDPM size of 64 x 64 pixels. Instead, we train it to effectively segment images sized 256 x 256 pixels. This is a significant advancement since the original DDPM works exclusively with 64x64 image sizes and is primarily designed for generating random image samples. In our work, we address both limitations with a novel, efficient approach for accurate retinal image segmentation. A comprehensive evaluation of our methodology includes both quantitative and qualitative assessments. Our proposed method demonstrates competitive performance compared to state-of-the-art techniques, as indicated by both qualitative and quantitative scores. The source code of our method can be accessed at https://***/AAleka/DDPM-segmentation.

关键词： Retinal image Segmentation Denoising Diffusion Probabilistic Models Medical Imaging machine vision image Super-resolution

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International conference on Algorithm, Imaging processing, and machine vision, AIPMV 2023

International Conference on Algorithm, Imaging Processing, a...

引用

2023 International conference on Algorithm, Imaging processing, and machine vision, AIPMV 2023

ISBN: (纸本)9781510672444

The proceedings contain 104 papers. The topics discussed include: image segmentation of rail surface defects based on fractional order particle swarm optimization 2D-Otsu algorithm;research on intelligent design algorithm of indoor space based on hybrid recommendation model;research on rule engine optimization algorithm in internet of things teaching platform;target allocation method based on multi-objective particle swarm optimization algorithm;pedestrian object detection algorithm based on lightweight YOLOv7 in complex street scenarios;safety risk assessment method of key personnel in infrastructure projects based on image data coupling identification;detection algorithm for diabetic retinopathy based on ResNet and transfer learning;research and implementation of efficient retrieval algorithm in big data environment;research on UAV path planning based on snake optimization algorithm;research on collaborative and integrated resource scheduling algorithm in heterogeneous cloud environment;and development and application of virtual synchronization system for live working robots based on binocular vision.

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Optimum Selection of image Object Attributes for Object-Based image Analysis and High Classification Accuracy 8th

Optimum Selection of Image Object Attributes for Object-Base...

引用

8th International conference on Computer vision and image processing (CVIP)

作者： Khadanga, Ganesh Jain, Kamal IIT Roorkee Roorkee 247667 Uttar Pradesh India

ISBN: (纸本)9783031581731;9783031581748

Object-based image analysis (OBIA) is extensively used for the classification of High-Resolution Satellite imagery (HRSI). The various attributes of the image segments like spectral, spatial and textural, can be generated for analysis and classification purposes. However, the use of all these attributes may not lead to attaining high classification accuracy. Experiments have shown that, a suitable set of these features need to be identified for faster and accurate classification of imageries. The filter based methods likeChi-Square, Information-gain and ReliefF are extensively used for identification and ranking the best set of parameters. The random tree based Boruta machine learning feature ranking method is also used in identifying the feature ranking along with the above algorithms. Subsequently, a learner is fused with a filter and the resultant receiver operating characteristic (ROC) plot of the model has been used to identify the best accuracy and the minimal set of attributes for identifying an individual feature like roads, trees, grass, buildings and shadow. The best set of parameters for a class is identified by the best ROC plot. The best parameters are identified from Boruta feature analysis. The results indicate that the identified smaller feature set helps in enhancing classification accuracy.

关键词： HRSI OBIA Boruta Feature Selection SVM

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3D Information in Robot vision System Based on Artificial Neural Network 14th

3D Information in Robot Vision System Based on Artificial Ne...

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14th International conference on Frontier Computing, FC 2024

作者： Liu, Xiaoxiao Department of Mechanical and Electrical Engineering Jinan Engineering Vocational Technical College Shandong Jinan China

ISBN: (纸本)9789819627974

In the exploration of robot vision systems based on artificial neural networks, the research mainly focuses on their applications in 3D information recognition and processing. By simulating the processing of the human visual system, this technology enables robots to more effectively interpret and understand the three-dimensional spatial information of their environment, which has a revolutionary role in robot navigation, object recognition, obstacle avoidance and the execution of complex tasks. And this technology shows great potential in many fields such as industrial automation, autonomous vehicles, drone monitoring, and service robots. Not only that, it also plays a very important role in providing in-depth information, accurate positioning and efficient decision-making applications. According to the experimental data, among the 800 experimental subjects, more than 754 people were satisfied with the recognition accuracy, recognition speed, machine efficiency improvement, image recognition clarity, and overall satisfaction with the system. These findings indicate that with the continuous advancement of technology, 3D vision systems based on artificial neural networks will show more significant performance and value in future applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： machine vision

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Experimental Study on Vortex-Induced Motion of Spar-Type Floating Offshore Wind Turbine Based on image processing Technology

Experimental Study on Vortex-Induced Motion of Spar-Type Flo...

引用

2023 International conference on Algorithm, Imaging processing, and machine vision, AIPMV 2023

作者： Wang, Yuhong Xia, Haishan Xiao, Yanghong Li, Lei Ocean College Zhejiang University Zhoushan316021 China School of Naval Architecture and Maritime Zhejiang Ocean University Zhoushan316022 China

ISBN: (纸本)9781510672444

Most floating wind turbine foundations consist of single or multiple columns, which are prone to vortex-induced motion (VIM) under the action of uniform flow. VIM is the main reason causing fatigue damage to mooring structures. Exploring the motion response of VIM of the spar-type wind turbine structure, the spar wind turbine foundation was designed as a prototype, and the model was simplified to a cylinder. In this paper, we conducted an experimental study of its model in the circulating water tank based on Matlab image processing technology. The VIM characteristics of the model were discussed by capturing its optical measurement points, and then the structural response amplitude was obtained by using the target tracking method. The study showed that the optical measurement method could effectively monitor the motion response of the structure, and the binary method could better obtain the VIM characteristics of the structure. Meanwhile, it was found that the response amplitude of the cylindrical VIM presents four stages: initial excitation branch, upper branch, lower branch, and desynchronization. It was also revealed that the maximum amplitude was reached in the upper branch, and the locking phenomenon was shown at the reduced velocity 4.96 ≤ Ur ≤ 7.11. © 2024 SPIE.

关键词： Water tanks

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Consistency Comparison of machine vision images Based on Improved ORB Algorithm 4th

Consistency Comparison of Machine Vision Images Based on Imp...

引用

4th International conference on machine Learning, image processing, Network Security and Data Sciences (MIND)

作者： Huang, Yong Henan Inst Sci & Technol Sch Informat & Engn Xinxiang 453003 Henan Peoples R China

ISBN: (纸本)9783031243660;9783031243677

In recent years, with the continuous development of society, people's exploration in the field of machine vision images has gradually increased the demand for machine vision and digital image processing. Only the consistency comparison research of machine vision images based on the improved ORB algorithm, in order to obtain more complete image information. Based on the improved ORB algorithm, this paper conducts research by improving the consistency comparison of machine vision images, and meets the requirements of accuracy and precision for the obtained machine vision images and so on. This paper briefly introduces the technology and development trend of machine vision image consistency comparison, studies the machine vision image consistency comparison, and through a series of experiments to prove that the machine vision image consistency comparison based on the improved ORB algorithm is effective in To a certain extent, it has certain feasibility in terms of precision and accuracy. Analysis and comparison based on different image stitching methods were carried out. The final results of the research show that the accuracy of the five-consistency comparison of machine vision images is 98.7% when the distance of image five is 83.4 km. Experimental data show that the accuracy of machine vision image consistency comparison has always been maintained at a stable level, that is, 97%. It shows that the accuracy of machine vision image consistency comparison does not decrease with the increase of distance.

关键词： ORB algorithm machine vision image consistency Comparison research

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image Deraining with Frequency-Enhanced State Space Model 17th

Image Deraining with Frequency-Enhanced State Space Model

引用

17th Asian conference on Computer vision, ACCV 2024

作者： Yamashita, Shugo Ikehara, Masaaki Keio University Yokohama Japan

ISBN: (纸本)9789819609109

Removing rain degradations in images is recognized as a significant issue. In this field, deep learning-based approaches, such as Convolutional Neural Networks (CNNs) and Transformers, have succeeded. Recently, State Space Models (SSMs) have exhibited superior performance across various tasks in both natural language processing and image processing due to their ability to model long-range dependencies. This study introduces SSM to image deraining with deraining-specific enhancements and proposes a Deraining Frequency-Enhanced State Space Model (DFSSM). To effectively remove rain streaks, which produce high-intensity frequency components in specific directions, we employ frequency domain processing concurrently with SSM. Additionally, we develop a novel mixed-scale gated-convolutional block, which uses convolutions with multiple kernel sizes to capture various scale degradations effectively and integrates a gating mechanism to manage the flow of information. Finally, experiments on synthetic and real-world rainy image datasets show that our method surpasses state-of-the-art methods. Code is available at https://***/ShugoYamashita/DFSSM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image reconstruction

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Representation Extraction Using Hyperbolic Knowledge Distilled Framework - An Industrial Application on High Risk Environment 16

Representation Extraction Using Hyperbolic Knowledge Distill...

引用

16th International conference on Computer and Automation Engineering (ICCAE)

作者： Kumar, Vijeth Murugesan, Malathi Veneri, Giacomo Baker Hughes Bangalore India Baker Hughes Florence Italy

ISBN: (纸本)9798350370058;9798350370164

We propose a computer vision architecture based on Hyperbolic networks, contrastive learning and knowledge distillation to detect unsafe behavior in energy production and oil & gas plants. Data scarcity poses a significant challenge to develop machine learning applications in industry. Indeed, the data may be incomplete, inconsistent, or biased, making it difficult to develop accurate and reliable models. Insufficient data during training phase has direct impact on the models' representation learning capabilities;with the aid of vision Transformers (ViTs), we are able to solve data crunch situations by learning efficient representations of the existing data. We harnessed the power of ViTs, as it incorporates more global information, leading to quantitatively stronger intermediate feature representations. Further, we approached the task with contrastive learning and obtained pairs of samples which are similar, to tackle the limited data availability in our industrial use case. The proposed approach by applying hyperbolic embeddings helps in extracting complex relationships in the data. Furthermore, the size of the model makes it suitable for devices with low computational capabilities such as unmanned robots.

关键词： Hyperbolic networks Contrastive Learning and Knowledge Distillation image processing image Understanding vision Transformers (ViTs) Data Scarcity

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Research on Automatic Workpiece Sorting System Based on machine vision 3

Research on Automatic Workpiece Sorting System Based on Mach...

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2023 IEEE 3rd International conference on Data Science and Computer Application, ICDSCA 2023

作者： Ji, Linfeng Zhenjiang Vocational Technical College Zhenjiang China

ISBN: (纸本)9798350341546

This paper expounds the automatic recognition method of parts based on computer vision. The feature database of the processed parts is constructed by using machine learning method. image preprocessing, threshold segmentation, edge and contour extraction are used to analyze the features of the image of the inspected part to judge whether the inspected part is qualified or not. Aiming at the attitude error generated when the workpiece is placed, a method for positioning the center of gravity and rotation angle of the workpiece based on boundary detection and contour tracking is proposed. Use the similarity measure to determine the characteristics of the object to be processed. Simulation results show that the method proposed in this paper is effective. © 2023 IEEE.

关键词： image processing machine vision pattern recognition workpiece

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A Research and Construction of Automatic Classification System for Environmental Art Renderings Based on Computer vision

A Research and Construction of Automatic Classification Syst...

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2023 International conference on Data Science and Network Security, ICDSNS 2023

作者： Chen, Yan Dalian Art College Dalian China

ISBN: (纸本)9798350301595

To address the classification challenge for environmental art renderings, this paper presents an automated classification system utilizing Computer vision techniques and employing vector machine support. Firstly, the concept of the technology related with Computer vision and image processing are briefly introduced. Then, we analyze the construction idea of the system, and provide the selection method of image features, extraction method image features, processing method before inputting data, and design process of classifier. At last, we find out the the normalization method and the rationality of kernel function selection through the experiments. And also, the automatic classification of environmental art renderings is realized. The proposed system model has a high accuracy rate of classification. © 2023 IEEE.

关键词： Computer vision

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