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

共 16347 条记录，以下是591-600 订阅

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Enhancing Vehicle Analysis with Fine Estimation on Video Streams Using image processing Techniques

Enhancing Vehicle Analysis with Fine Estimation on Video Str...

引用

2023 Annual International conference on Emerging Research Areas: International conference on Intelligent systems, AICERA/ICIS 2023

作者： Radha, R. Reddy, Kotha Bhargavi Yeshwanth, R. Alliance University Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350303452

Enhancing Vehicle Analysis with fine Estimation on video streams time object detection and tracking, and OCR for license plate recognition. By leveraging YOLO, the project extracts precise vehicle information from video streams, enabling comprehensive data collection for traffic analysis. Additionally, OCR algorithms automatically identify license plate numbers, facilitating law enforcement and fine estimation. This integrated approach enhances vehicle analysis, providing valuable insights for traffic optimization, infrastructure planning, and law enforcement strategies. The project aims to create safer, more efficient cities by harnessing the power of image processing techniques like YOLO and OCR in realtime vehicle analysis. © 2023 IEEE.

关键词： Optical character recognition

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AI-Generated image Detection using a Cross-Attention Enhanced Dual-Stream Network

AI-Generated Image Detection using a Cross-Attention Enhance...

引用

Asia-Pacific-Signal-and-Information-processing-Association Annual Summit and conference (APSIPA ASC)

作者： xi, Ziyi Huang, Wenmin Wei, Kangkang Luo, Weiqi Zheng, Peijia Sun Yat Sen Univ GuangDong Prov Key Lab Informat Secur Technol Guangzhou Peoples R China

ISBN: (纸本)9798350300673

With the rapid evolution of AI Generated Content (AIGC), forged images produced through this technology are inherently more deceptive and require less human intervention compared to traditional Computer-generated Graphics (CG). However, owing to the disparities between CG and AIGC, conventional CG detection methods tend to be inadequate in identifying AIGC-produced images. To address this issue, our research concentrates on the text-to-image generation process in AIGC. Initially, we first assemble two text-to-image databases utilizing two distinct AI systems, DALL center dot E2 and DreamStudio. Aiming to holistically capture the inherent anomalies produced by AIGC, we develope a robust dual-stream network comprised of a residual stream and a content stream. The former employs the Spatial Rich Model (SRM) to meticulously extract various texture information from images, while the latter seeks to capture additional forged traces in low frequency, thereby extracting complementary information that the residual stream may overlook. To enhance the information exchange between these two streams, we incorporate a cross multi-head attention mechanism. Numerous comparative experiments are performed on both databases, and the results show that our detection method consistently outperforms traditional CG detection techniques across a range of image resolutions. Moreover, our method exhibits superior performance through a series of robustness tests and cross-database experiments. When applied to widely recognized traditional CG benchmarks such as SPL2018 and DsTok, our approach significantly exceeds the capabilities of other existing methods in the field of CG detection.

关键词： image resolution

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Application of Novel Memristor Chaotic System in image Encryption 4

Application of Novel Memristor Chaotic System in Image Encry...

引用

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

作者： Gao, Huiyan Cai, Zhenyang Xu, Hongmei Yanbian University The New Generation of Electronic Information Technology Yanji China

ISBN: (纸本)9798350361643

Memristors, also known as variable resistors, are often used in research in fields such as neural networks, nonlinear systems, and digital circuits due to their memory, resistivity, and nonlinear characteristics. Because the combination of memristor and chaotic system can effectively improve the complexity and unpredictability of the system, and provide security for data processing. Therefore, applying the memristive chaos system to image encryption can not only enrich the diversity of encryption algorithms, but also meet the requirements for randomness and diffusion in the encryption process, effectively improving the security of the algorithm and achieving efficient encryption. Based on the nonlinear characteristics of memristor, this paper designs a new five-dimensional memristor chaotic system by combining memristor and chaotic system, then, designs an image encryption scheme based on this memristor chaotic system. The security of the encryption process is verified. © 2024 IEEE.

关键词： Memristors

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Design and Implementation of an AI-Driven Hybrid Framework for Risk Assessment 7

Design and Implementation of an AI-Driven Hybrid Framework f...

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7th International conference on Advanced algorithms and Control Engineering, ICAACE 2024

作者： Zhang, Haibo Yang, xi School Of Economics And Management Southwest University Of Science And Technology Dept. Of Economics And Management Mianyang China

ISBN: (纸本)9798350361445

This paper discusses key challenges of data processing in the field of artificial intelligence (AI), specifically in dealing with unstructured data and adapting to market changes. We propose a novel AI risk assessment framework by developing a multi-model hybrid scoring system that integrates machine learning and deep learning, focusing on random forests and long Short-Term memory (LSTM) networks. Experimental validation shows that our framework performs more effectively in accurate risk classification compared with existing SOTA methods, significantly enhancing the capabilities of AI systems in complex data environments. Our results provide a new perspective and technical approach for AI risk assessment, which plays a crucial role in the optimization and application of AI systems. © 2024 IEEE.

关键词： Long short-term memory

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Research on the Application of Computer 3D Technology in the Creation of Films Adapted from Literary Works

Research on the Application of Computer 3D Technology in the...

引用

2022 IEEE Asia-Pacific conference on image processing, Electronics and Computers, IPEC 2022

作者： Song, Lei Xi'an Traffic Engineering Institute Xi'an710300 China

ISBN: (纸本)9781665409025

The article studies the adaptation of literary works to animated films. Discuss the importance of the adaptation of literary works to the creation of animated films. A new method of using the Poly (polygonal geometric modeling) function of 3DSMAX 3D graphics software in the production of film and television physical special effects models is described. We analyzed the needs of platform development in detail, planned various functional modules, worked out the development process of virtual movie computer three-dimensional animation special effects model, and then through comparison, we chose 3Dmax, Unity3D and other related software to develop the entire system. Finally, the article analyzes and compares the impact of depth map preprocessing under different filtering algorithms on the view quality of literary works adapted from movies, and three fast algorithms in inter-frame motion estimation. © 2022 IEEE.

关键词： Motion pictures

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Low Light image Enhancement Algorithm Based on Retinex Model Learning 6

Low Light Image Enhancement Algorithm Based on Retinex Model...

引用

6th International conference on Artificial Intelligence and Pattern Recognition, AIPR 2023

作者： Liu, Weihua Zhang, Xuhui Yi, Chen School of Communication and Information Engineering Xi'an University of Posts and Telecommunications Shaanxi Provincial Forensic Science Electronic Information Research Center Shaanxi Prov. Intl. Joint Research Center for Wireless Communication and Information Processing China School of Communication and Information Engineering Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

Low-light images have low contrast and unclear details, resulting in the reduction of available information for human vision. The current mainstream enhancement algorithms have problems such as noise amplification, color distortion, and dependence on data sets during the enhancement process. Therefore, a low-light image enhancement algorithm based on Retinex model and deep learning is proposed. First, the proposed residual network cascade is applied to the decomposition network based on Retinex theory to improve the gradient disappearance problem of the deep neural network, and at the same time obtain the illumination and reflection components of the image. Secondly, an adaptive gamma transformation function is designed to enhance the illumination component, which can effectively improve the low contrast problem of the image;since the noise in the dark area is amplified during the enhancement process, a full-scale learning network is designed to improve the image quality. The reflection component is denoised. Finally, the enhanced illumination component and reflection component are fused to obtain the final enhanced image. In the data set test results, the peak signal-to-noise ratio of the proposed algorithm is improved by an average of 0.33dB compared with the mainstream algorithm Zero-DCE, and by an average of 0.48dB compared with the URetinex-Net algorithm. The experimental results show that the algorithm can effectively improve the brightness of the image while reducing the image noise and accurately restore the texture information of the image. © 2023 ACM.

关键词： image enhancement

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The Major Challenge in Improving image Dark Channel Defogging Algorithm 23

The Major Challenge in Improving Image Dark Channel Defoggin...

引用

6th International conference on Information Science and systems, ICISS 2023

作者： Samonte, Mary Jane C. Wang, Rongfu Li, Shuhua School of IT Mapua University Manila Philippines

ISBN: (纸本)9798400708206

With the rapid development of computer vision and image processing technology, scene image processing under particular weather conditions has become an important research direction, especially in foggy conditions of the image, which is easily affected by haze, resulting in unclear picture quality and image information loss. The defogging algorithm came into being to solve this kind of image problem. This paper analyzes the advantages and disadvantages of dark channels and histogram algorithms. Given the time and space complexity and incomplete fog removal of the dark channel and histogram algorithm, a combined improved algorithm is proposed, a fast fog removal algorithm combining dark channel and histogram enhancement. The analysis of experimental results shows that the fast-defogging algorithm combined with dark channel and histogram enhancement proposed in this paper can restore better visual effects and preserve edge details. Especially in the distant image area, image details are easier to obtain, and the time and space complexity of the algorithm is reduced. © 2023 ACM.

关键词： image enhancement

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Space-Earth Integration Network Slice Mapping Based on Multi-Level Attribute Representation Model 8

Space-Earth Integration Network Slice Mapping Based on Multi...

引用

8th International conference on Signal and image processing, ICSIP 2023

作者： Qu, Hua Wu, Siying Zhao, Jihong Ren, Yayun Mao, Lin Wang, Siyan Xi'An Jiaotong University College of Software Engineering Xi'an China

ISBN: (纸本)9798350397932

Most of the existing network slicing methods only consider a single attribute of network nodes and ignore the overall network attributes, however, due to the different characteristics of network resources, complex node, link and topology states, a wide variety of services, etc., these algorithms may lead to a declining acceptance rate of network slicing and cannot better meet business requirements. To solve these problems, this paper provides a multi-level attribute representation model for Space-Earth Integration Network and a network slicing algorithm based on this model, called M-ARM, which considers multiple attribute characteristics of network slicing nodes. In the first stage, this method uses the resource attributes, topological attributes, location attributes and security attributes of the network slicing nodes to build the multi-level attribute representation model. In the second stage, this model is used to calculate multi-criteria decision metrics and perform node ranking, then the node mapping process in the network slice is performed based on the results of the node rank, and in the third stage, the node location deployment probability is designed and the link mapping process in the network slice is performed using the K-shortest path algorithm to avoid link congestion since frequent shortest path selection. Finally, the results of this algorithm are compared with other algorithms using simulation and simulation experiments. The experiment results show that this algorithm enhances the acceptance rate of network slicing and achieves fine-grained control of the network by the underlying infrastructure resources of the network operator matching the actual service. © 2023 IEEE.

关键词： Mapping

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Traffic Sign Recognition by image Preprocessing and Deep Learning 15th

Traffic Sign Recognition by Image Preprocessing and Deep Lea...

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15th International conference on Intelligent Human-Computer Interaction (IHCI)

作者： Khamdamov, U. R. Umarov, M. A. Khalilov, S. P. Kayumov, A. A. Abidova, F. Sh. Univ Management & Future Technol Tashkent Uzbekistan Tashkent Univ Informat Technol Samarkand Branch Tashkent Uzbekistan Tashkent Univ Informat Technol Tashkent Uzbekistan

ISBN: (纸本)9783031538292;9783031538308

Due to the improvement in the car manifacture, the rate of road traffic accidents is increasing. To solve these problems, there is loads of attention in research on the development of driver assistance systems, where the main innovation is traffic sign recognition (TSR). In this article, a special convolutional neural network model with high accuracy compared to traditional models is used for TSR. The Uzbek Traffic Sign Dataset (UTSD) applied in the zone of Uzbekistan was created, consisting of 21.923 images belonging to 56 classes. We proposed a parallel computing method for real-time processing of video haze removal. Our utilization can process the 1920 x 1080 video series with 176 frames per second for the dark channel prior (DCP) algorithm. 8.94 times reduction of calculation time compared to the Central processing Unit (CPU) was achieved by performing the TSR process on the Graphics processing Unit (GPU). The algorithms used to detect traffic signs are improved YOLOv5. The results showed a 3.9% increase in accuracy.

关键词： Traffic sign recognition deep learning image dehazing UTSD dataset parallel processing data augmentation

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A HVDC System Fault Diagnosis Method Based on PSO-LightGBM Algorithm

A HVDC System Fault Diagnosis Method Based on PSO-LightGBM A...

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International conference on Vision, image and Signal processing (ICVISP)

作者： Zhanjun Huang Maning Zhang Jun xie Yiting Wang School of Aeronautics Northwestern Polytechnical University Xi'an China National Key Laboratory of Aircraft Configuration Design Xi'An China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

Due to the complexity of their structure and the particularity of their application environments, aircraft High-Voltage Direct Current (HVDC) systems are prone to faults, with inter-module failures complicating fault diagnosis. To address this issue, a fault diagnosis method for HVDC systems has been developed. Feature extraction methods were designed for the rectifier, BUCK converter, and inverter, respectively, with the sum-to-amplitude ratio of signals selected as a feature for the rectifier; multi-scale skewness was proposed for the BUCK converter; and the ratio of the signal's average to peak absolute value was chosen for the inverter. Subsequently, the PSO-LightGBM algorithm was proposed, which employs the LightGBM algorithm for classification and utilizes a particle swarm algorithm to optimize the parameters of the LightGBM, establishing the optimal model. The experimental results demonstrate that the proposed method can accurately achieve fault diagnosis in HVDC systems.

关键词： Fault diagnosis Buck converters HVDC transmission Atmospheric modeling Signal processing algorithms Rectifiers Feature extraction Inverters Classification algorithms Aircraft

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