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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

3rd World Conference on Intelligent and 3D Technologies, WCI...

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3rd World conference on Intelligent and 3D Technologies, WCI3DT 2024

ISBN: (纸本)9789819791231

The proceedings contain 45 papers. The special focus in this conference is on Intelligent and 3D Technologies. The topics include: Multi-scale Point Cloud Shape Completion Network Based on Deep Learning;research on Application and Effect Evaluation of Product Innovation Management Based on Deep Learning;study on Deep Learning-Based Personalised Product Recommendation Model for Autonomous Question-and-Answer Robot;application of image Watermarking Technology Based on Deep Learning in Copyright Protection;research on the Combination of Building Structural Health Monitoring and Deep Learning image processing;electrical Equipment Prediction in a Variable Electromagnetic Field Using Deep Learning;state Monitoring and Fault Prediction of Wind Farm Transmission and Transformation Equipment Based on Deep Learning;application of Deep Learning algorithms in the Innovation Ecosystem of Electric Power;optimization Strategy for Inventory Management Based on Machine Learning;intelligent Design and Evaluation of Aging Adaptable Public Spaces Based on Deep Learning;performance Optimization and Acceleration of Machine Learning algorithms in Task Allocation of Mine Maintenance Robots;Application of Deep Learning to Improve the Performance of Automotive Electronic Control Unit (ECU);deep Learning-Based Scene Classification for Remote Sensing images;Improved Swarm Intelligence Optimization Algorithm Based on SL-Relu Activation Function Improvement Strategy and Its Application in Price Forecasting;Automatic Segmentation of Traumatic Penumbra in Rat Brain Based on Improved UNet++;A Brain Tumor Classification Method Based on ResNeXt-SESA Network;A LSTM Algorithm for Coastal City Cultural Scene Value Sustainable Development Forecast Improvement;pattern Recognition in Archive Analysis Using Data Mining;building Crack Detection Method Based on Convolutional Neural Network.

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A Live Demo of Single-Photon Imaging and Applications

A Live Demo of Single-Photon Imaging and Applications

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SIGGRAPH conference on Emerging Technologies

作者： Jungerman, Sacha Sundar, Varun Gupta, Mohit Univ Wisconsin Madison Madison WI 53706 USA

ISBN: (纸本)9798400705243

Single-photon sensors are a novel class of imaging sensors that are sensitive to the individual arrival of photons. In recent years, single-photon sensors have witnessed rapid growth in key sensor characteristics such as array resolution, which, for the first time, has made computer vision and imaging with these emerging sensors possible. This rapid growth has also spurred the development of algorithms that can harness the rich spatio-temporal scene information captured by single-photon sensors, which has led to several new imaging capabilities. These capabilities include imaging in challenging SNR conditions, high-dynamic range imaging, compensating extreme camera motion extents, and even providing the functionality of numerous imaging systems via post-capture processing. Our demo will showcase these exciting capabilities to a wide computer vision and graphics audience, and in doing so, make a case for the mainstream adoption of single-photon technology.

关键词： Single-photon camera single-photon avalanche diode quanta image sensors high dynamic range high-speed imaging low-light imaging motion compensation software-defined cameras.

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Quantum Computing in image processing 1

Quantum Computing in Image Processing

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1st International conference on Recent Developments in Electronics and Communication systems, RDECS 2022

作者： Sachdeva, Kumud Sachdeva, Rajan Gupta, Himanshu Department of Computer Science and Engineering Chandigarh University Punjab Gharuan140413 India

ISBN: (纸本)9781643683607

If you read that quantum machine learning applications solve some traditional machine learning problems at an amazing speed, be sure to check if they return quantum results. Quantum outputs, such as magnitude-encoded vectors, limit the use of applications and require additional specifications on how to extract practical and useful results. In satellite images, degradation of image contrast and color quality is a common problem, which brings great difficulties for information extraction and visibility of image objects. This is due to atmospheric conditions, which can cause a loss of color and contrast in the image. Regardless of the band, image enhancement plays a vital role in presenting details more clearly. The research includes new computational algorithms that accelerate multispectral satellite imagery to improve land cover mapping and study feature extraction. The first method is a quantum Fourier transform algorithm based on quantum computing, and the second method is a parallel modified data algorithm based on parallel computing. These calculation algorithms are applied to multispectral images for improvement. The quantum-processed image is compared with the original image, and better results are obtained in terms of visual interpretation of the extracted information. Quantitatively evaluate the performance of the improved method and evaluate the applicability of the improved technology to different land types. © 2023 The authors and IOS Press.

关键词： image enhancement

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A GPU Parallel Stitching Algorithm for Low-Altitude Parallax Scenes

A GPU Parallel Stitching Algorithm for Low-Altitude Parallax...

引用

Machine Learning and Computer Application (ICMLCA), International conference on

作者： Sha Liu Shan Zhou Yan Hu China Electronics Technology Group Corp 54th Research Institute Shijiazhuang China China Electronics Technology Group Corp 20th Research Institute Xi'an China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

Panorama stitching of low-altitude captured images is a very interesting and challenging task. Since 3D scenes are not planar, there may be significant changes in the relative positions of scene structures in each perspective in the images, thus causing parallax. Existing image stitching algorithms often fail in parallax scenes and are not efficient enough to meet the real-time processing requirements of drones. To address this problem, we introduce gridded dense projection estimation and design a parallel computing unit suitable for GPUs for rapid modeling of projection fields. Experimental results show that our algorithm significantly outperforms the comparison algorithms in terms of computational performance, has high real-time performance, and achieves nearly the same level of stitching quality and naturalness.

关键词： Three-dimensional displays Computational modeling Graphics processing units Machine learning Parallel processing Real-time systems Partitioning algorithms Computational efficiency image stitching Periodic structures

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Comparative Analysis of CNN Architectures for Enhancing Oral Cancer Detection Using Advanced image processing Techniques 8

Comparative Analysis of CNN Architectures for Enhancing Oral...

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8th IEEE International conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Rathi, Snehal Puranik, Atharva Pratham, Shaantanu Kulkarni, Vibhav Chincholkar, Harshvardhan Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350391770

To effectively diagnose oral cancer, sophisticated technologies like deep learning must be investigated. This is still a significant difficulty in medical diagnostics. To assess Convolutional Neural Network (CNN) architectures' efficacy in oral cancer detection, we compare and contrast them in this research. Specifically, we compare the performance of VGG19, ResNet50, ResNet101, and a standard CNN model using a dataset of Oral Cancer (Lips and Tongue) images (OCI). We use sophisticated image processing methods including data augmentation, contrast improvement, and noise reduction to improve the quality of the supplied data. We use accuracy, precision rate, recall rate, and F1-score as our assessment measures. Our findings show that the suggested CNN design outperforms VGG19 (72.97%), ResNet50 (79.73%), and ResNet101 (71.62%) in terms of accuracy, with a maximum of 87.10%. Moreover, our approach shows excellent recall, F1score, and accuracy, highlighting its efficacy in correctly detecting malignant areas in oral pictures. Through this comparative analysis, we provide valuable insights into the suitability of different CNN architectures for oral cancer detection, without the integration of specific optimization algorithms. Our findings highlight the potential of deep learning techniques to improve treatment outcomes and early diagnosis for patients with oral cancer, ultimately leading to the advancement of computer-aided cancer detection (CAD) systems. © 2024 IEEE.

关键词： Convolutional neural networks

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Insulator Defect Detection Technology Based on Deep Learning 4

Insulator Defect Detection Technology Based on Deep Learning

引用

4th International conference on Energy Engineering and Power systems, EEPS 2024

作者： Dang, Qian Shang, Wenbo Luo, Fazheng Lu, Pengdong Lin, Guobin Gui, xiaolin State grid Gansu electric power Company Digitalization division Lanzhou China Xi'an Jiaotong University Faculty of electronic and information engineering Xi'an China

ISBN: (纸本)9798350366914

With the development of power system, the number and scale of power equipment continue to expand, and the risk of equipment failure is also increasing. Therefore, timely and accurate fault detection becomes particularly important. As a key part of high-voltage transmission lines, insulators are exposed to complex and variable outdoor environments for a long time, and are susceptible to faults or defects due to various factors. In the traditional power grid system, the maintenance of high-voltage transmission lines usually relies on manual patrol, which has security risks and high costs. However, the development of UAV technology and image recognition technology provides a better solution for insulator defect detection. Compared with the traditional manual patrol, the UAV patrol strategy significantly improves the detection efficiency and security, and even can realize remote monitoring and real-time early warning of the power grid system. Based on YOLOv8 target detection algorithm, this paper conducts an in-depth study on insulator defect detection technology. In order to enhance the recognition ability of the model for important features, this paper adds the CBAM attention mechanism to the YOLOv8 algorithm. This mechanism combines spatial attention and channel attention, so that the model can capture and focus on important features more accurately, thereby improving the detection accuracy of insulator defects. At the same time, in order to solve the problem of incomplete identification of small targets in defect detection, this paper adds a small target detection head to improve the detection ability of the model for small targets and ensure the comprehensiveness and accuracy of insulator defect detection. Finally, ablation experiments verify the effectiveness of the proposed method in detecting insulator defects, and a series of comparative experiments are carried out with several mainstream target detection algorithms. The experimental results show that the impro

关键词： Smart power grids

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A Double-stream Exchange Transformer Network for Intrinsic image Decomposition

A Double-stream Exchange Transformer Network for Intrinsic I...

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2022 International conference on image processing and Media Computing, ICIPMC 2022

作者： Zhang, Feng Jiang, xiaoyue xia, Zhaoqiang Gabbouj, Moncef Peng, Jinye Feng, xiaoyi Northwestern Polytechnical University School of Electronics and Information Xi'an China Tampere University Department of Computing Sciences Tampere Finland Northwestern University School of Information Science and Technology Xi'an China

ISBN: (数字)9781665468725

ISBN: (纸本)9781665468725

Intrinsic image decomposition separates the input image into several layers which reflect the attributes of the scene. In this paper, we present a double-stream exchange transformer network for intrinsic image decomposition, in which an independent and interrelated relationship is built between reflectance and shading. There are two core designs in the double-stream exchange transformer network (DSETNet). First, we propose a novel exchange transformer block, which performs the information exchange and reconstruction between reflectance and shading components in a window-based self-attention. Second, a residual structure is added into the exchange transformer block to form a residual exchange transformer block to eliminate artifacts caused by local window areas. We predict reflectance and shading constraint relationship between reflectance and shading is established through residual exchange transformer block. The evaluation results on two real and synthetic public datasets BOLD and ShapeNet show that the DSETNet achieves competitive results with other advanced algorithms. © 2022 IEEE.

关键词： Reflection

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People Counting System Using OpenCV algorithms and Edge Computing for Safety Management

People Counting System Using OpenCV Algorithms and Edge Comp...

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2023 IEEE International conference on Smart Information systems and Technologies, SIST 2023

作者： Seitbattalov, Zhexen Y. Canbolat, Huseyin Atanov, Sabyrzhan K. Moldabayeva, Zhanar S. Kyzyrkanov, Abzal E. Maidanov, Adil K. L. N. Gumilyov Eurasian National University Department of Computer and Software Engineering Astana Kazakhstan Ankara Yildirim Beyazit University Department of Electrical and Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350335040

The necessity of ensuring people's safety in urban conditions during gathering in a certain indoor or outdoor area, as well as during the operation of technical equipment, requires measurement of their number, weights, the distance between them, density and many other parameters. The collection of those parameters and analysis allows you to ensure the optimal numerical value of people per area and not exceed the critical peak value, ensuring the safety of people's health and life. However, automating those processes requires stable network bandwidth and enormous computing resources for data transferring to the data center and its processing, as well as applying artificial intelligence algorithms to the data and sending the results back to the end-user. In this paper, to avoid the disadvantages of cloud computing, we consider Raspberry Pi with a camera module as an edge device to develop an automated people-counting system based on using OpenCV algorithms and Edge Computing for Safety Management. The proposed system can be used for indoor or outdoor areas, during scaffolding works and lift's operation for controlling an optimal number of people. As a result of the application the edge computing, network bandwidth and computing resources of the data center have been optimized. © 2023 IEEE.

关键词： image processing

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Eight Points Geometric Constraint for Stereo Matching 9

Eight Points Geometric Constraint for Stereo Matching

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9th International conference on systems and Informatics, ICSAI 2023

作者： Wang, Yuanbin Xiamen Institute of Technology School of Data and Computer Science Xiamen361021 China

ISBN: (纸本)9798350383706

Stereo point matching is a critical and fundamental problem in 3D vision. Numerous algorithms have been proposed to solve this problem. Since images obtained from 3D to 2D projection of a 3D scene lose depth information of the 3D scene, there is no numerical geometric invariant between stereo images. So, we do not have similar algorithms that use geometric invariants for point matching as in the case of 2D to 2D projective transformations. However, it is discovered that geometric constraints can be used to restrict the search space and eliminate faulty correspondences. In this paper we derive a new mathematical constraint relating eight corresponding points in stereo images. It is a simple formula consisting of coordinates of the eight points that compute to zero for the eight points to be in correspondence. This constraint can be used as a preliminary necessity testing step before other time-consuming methods to speed up the matching procedure. © 2023 IEEE.

关键词： Stereo image processing

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A PLC-based three-dimensional warehouse simulation system 24

A PLC-based three-dimensional warehouse simulation system

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3rd International conference on Computer, Artificial Intelligence and Control Engineering, CAICE 2024

作者： Wu, Guichun Cai, Qingsheng Zhang, Zicheng Ling, Yifan Zhu, Lanchong Chen, Zhaoqi Guangzhou Xinhua University Dongguan523133 China

ISBN: (纸本)9798400716942

This paper presents an automated three-dimensional warehouse simulation system based on a programmable logic controller (PLC). The system is designed to simulate the automated operation of modern warehouses and provide a highly realistic simulation environment to support the development and testing of warehouse management systems (WMS) and human-machine interfaces (HMI). Through detailed system design and experimental validation, this paper demonstrates the potential of this simulation system to improve warehouse operation efficiency, optimize storage management processes, and enhance operator training. In terms of system architecture, we integrated PLC module, WMS and HMI to ensure real-time operation and accuracy. In particular, the PLC module works closely with the WMS through real-time data exchange to ensure the accuracy of inventory management, and the HMI is designed with a focus on user experience, providing an intuitive operator interface and real-time data visualization so that users can easily monitor and control the simulation process. Our research provides valuable insights into the design and optimization of automated warehouse systems, particularly in the areas of education and industrial training. © 2024 ACM.

关键词： Stereo image processing

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