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检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4813 条记录，以下是431-440 订阅

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Comprehensive study of image processing techniques for low-altitude target recognition 4

Comprehensive study of image processing techniques for low-a...

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4th international conference on computer Vision, image and Deep Learning, CVIDL 2023

作者： Shao, Jianming Yu, Ya Xu, Zheng Ye, Chen Yan, Minghao Tong, Yuhao State Grid Wuxi Power Supply Company Wuxi China Jiayuan Technology Co. Ltd Nanjing China

ISBN: (纸本)9798350326444

This article presents a comprehensive overview of image processing techniques for low-altitude target recognition. The analysis includes various algorithms that incorporate shape, texture, and motion features, highlighting their advantages, disadvantages, and applicability. Additionally, this article explores multiple methods for low-altitude target recognition based on multi-feature fusion, comparing their advantages and disadvantages, and discussing future technological development directions. The article serves as a valuable reference for researchers interested in low-altitude target recognition, providing insights on algorithm selection and the application of multi-feature fusion. The presented research is expected to contribute to the advancement of low-altitude target recognition technology. © 2023 ieee.

关键词： image processing

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Classification of image Classes Based on the PCA Algorithm Optimized by the KNN Algorithm Improved by Genetic Algorithms 6

Classification of Image Classes Based on the PCA Algorithm O...

引用

6th international conference on Information Communication and Signal processing, ICICSP 2023

作者： Doru, Constantin Costel, Balcau The National University of Science and Technology Politehnica Bucharest Piteşti Univ. Centre Department of Mathematics and Computer Science Romania

ISBN: (纸本)9798350339994

In this paper we propose an optimized version of the PCA algorithm by using genetic algorithms and the KNN technique with applications in the classification of image classes. The algorithm are developed by optimizing the images projection stage based on the eigenvectors that ensure the extraction of essential features from the data. In that stage, the optimal value regarding the size of the projection space of the initial images is determined by using a genetic algorithm and and the improved KNN algorithm regarding the key parameter represented by the number of nearest neighbors used in the testing stage. For the validation and testing of the developed algorithms, the classification of face image classes corresponding to several people is considered. The proposed algorithm includes several versions, analyzed in the experimental study, depending on the similarity measure used (the Euclidian distance, Manhattan distance, Mahalanobis distance, Minkowski distance and cosine) to determine the nearest neighbors to the KNN algorithm, as well as based on the crossover recombination method chosen at the level of binary genes with a crossover point or more many crossing points. The experimental study on the methods established in the work attests good performance through the percentages of correctness, resulting in applications for recognizing people through facial images. © 2023 ieee.

关键词： Digital image processing (DIP) Face Recognition (FR) Genetic Algorithms (GA) K-Nearest Neighbors (KNN) Principal Component Analysis (ICA)

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New image processing: VGG image Style Transfer with Gram Matrix Style Features 5

New Image Processing: VGG Image Style Transfer with Gram Mat...

引用

2023 5th international conference on Artificial Intelligence and computer applications, ICAICA 2023

作者： Zhang, Longqing Wang, Zishang He, Jinwen Li, Yixuan School of Computer Science Guangdong University of Science and Technology Dongguan China

ISBN: (纸本)9798350323313

Using CNN for style transfer is a powerful image processing technique. The goal of style transfer is to apply the style of one image to another image, creating a new image that retains the content of the original image but has a style similar to the other image. This is known as style transfer. The process begins by defining preprocessing and postprocessing functions for the images. Then, the VGG-19 model is used to extract image features, and the synthesized image is continuously updated by minimizing the loss function as model parameters. The loss function used in the experiment is a weighted combination of content loss, style loss, and total variation loss, which balances the relative importance of preserving content, transferring style, and reducing noise in the synthesized image. The style is expressed using the Gram matrix to represent the style layer outputs. The results indicate that the synthesized image retains the scenery and objects from the content image while simultaneously transferring the color palette from the style image. © 2023 ieee.

关键词： computer vision

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CNN-based perceptual hashing scheme for image groups suitable for security systems 47

CNN-based perceptual hashing scheme for image groups suitabl...

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47th ieee-computer-Society Annual international conference on computers, Software, and applications (COMPSAC)

作者： Sugawara, Yusei Meng Zhaoxiong Morizumi, Tetsuya Miyata, Sumiko Hosono, Kaito Kinoshita, Hirotsugu Kanagawa Univ Grad Sch Engn Yokohama Kanagawa 2218686 Japan TOME R&D Dev Dept 5 Near Future Solut Grp Yokohama Kanagawa 2400005 Japan Kanagawa Univ Fac Engn Yokohama Kanagawa 2218686 Japan Shibaura Inst Technol Fac Engn Tokyo 1358548 Japan

ISBN: (纸本)9798350326970

Perceptual hashing, which generates a message digest showing how humans perceive similarity in images, is suitable for ensuring the equivalence between a modified/edited image and the original. Conventional perceptual hashing is mainly utilized for similarity-based image retrieval and is not appropriate for image identification, which is required in security systems such as digital rights management. We previously developed a construction method for perceptual hashing in security systems that utilizes a convolutional neural network (CNN). In practical applications, multiple different images are published in various media forms (e.g., articles or books), so generating an identical message digest for each of these images simultaneously makes content management easier. Therefore, in this work we extend our earlier CNN-based perceptual hashing scheme so that it can generate an identical message digest for images in a group. This approach reduces the computational cost for fine-tuning CNN compared to generating a perceptual hash for each image in a group individually.

关键词： Perceptual Hashing Message Digest CNN Digital Rights Management

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Multi-Models from computer Vision to Natural Language processing for Cheapfakes Detection

Multi-Models from Computer Vision to Natural Language Proces...

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2023 ieee international conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Nguyen, Thanh-Son Tran, Minh-Triet University of Science VNU-HCM Viet Nam National University Ho Chi Minh City Viet Nam CyberCore AI Viet Nam

ISBN: (纸本)9798350313154

Cheapfakes can compromise the integrity of information and erode trust in multimedia content, making their detection critical. Identifying Out of Context misuse of media is essential to prevent the spread of misinformation and to ensure that news and information are presented accurately and ethically. In this paper, we focus our efforts on Task 1 of the Grand Challenge on Detecting Cheapfakes in ICME2023, which involves detecting triplets consisting of an image and two captions as Out of Context. We propose a new robust approach for detecting Cheapfakes, which are instances of image reuse with different captions. Our proposed approach leverages multi-models in computer vision and Natural language processing, such as Named entity recognition, image captioning, and Natural language inference. In our experiments, the proposed multi-models method achieves an impressive accuracy of 78.6%, the highest accuracy among the candidates on the hidden test set. Overall, our approach demonstrates a promising solution for detecting Cheapfakes and safeguarding the integrity of multimedia content. Our source code is public on https://***/thanhson28/***. © 2023 ieee.

关键词： computer vision

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A New Approach Monitoring Wind Turbine Clearance Based on image processing

A New Approach Monitoring Wind Turbine Clearance Based on Im...

引用

2023 ieee international conference on Electrical, Automation and computer Engineering, ICEACE 2023

作者： Shengqi, Lu Qian, Wang Weidong, Chen Qiteng Technology Wuhan Co. Ltd Department of New Energy CSSC Wuhan China

ISBN: (纸本)9798350309614

Wind turbine clearance refers to the minimum distance that must be maintained between the rotating blades of the wind turbine and the tower where the blades are installed. This clearance is very important to ensure the normal operation of the wind turbine. If the distance is too small, it may cause tower sweeping (blade impact on the tower), so it is necessary to monitor the clearance to ensure the normal operation of the wind turbine. At present, many methods based on image processing have been proposed to calculate the wind turbine clearance. Since the position of the wind generator tower in the image hardly change, the difficulty of the wind turbine clearance calculation based on image processing lies in accurately giving the profile of the blade. In this context, this paper not only integrates the traditional algorithm and deep learning algorithm, but also proposes an expansion filtering algorithm to improve the detection effect of the blade. We evaluate our method on the collected data set, the result shows that the method proposed in this paper is better than the traditional algorithm and deep learning. © 2023 ieee.

关键词： deep learning image processing wind turbine clearance

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An Efficient Anti-Tampering image Watermarking Algorithm with Low Distortion

An Efficient Anti-Tampering Image Watermarking Algorithm wit...

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2023 international conference on image processing and computer Vision, IPCV 2023

作者： Xie, Rongsheng Liu, Honghui School of Computer & Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9781665473941

The existing anti-tampering image digital watermarking algorithms are difficult to balance the performance of watermarked image quality, tampering detection and localization. The paper proposes an efficient anti-tampering image watermarking algorithm with low distortion. The proposed algorithm dualizes the efficients of the DWT transformed image, and then modifies the DWT efficients corresponding to the sequence of embedding positions using a low-loss strategy, with the result that the values of the dualized DWT efficients are exactly equal to the corresponding watermark bits. To improve the quality of the watermarked image, the chaotic key segmentation adaptive watermarking algorithm is further proposed. The experimental results show that the proposed algorithm can not only calculate the tampering rate, but also locate the tampering location, and the quality of the watermarked image is improved. © 2023 ieee.

关键词： Discrete wavelet transforms

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Hotspot Detection of Solar Photovoltaic System: A Perspective from image processing 3

Hotspot Detection of Solar Photovoltaic System: A Perspectiv...

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ieee 3rd international conference on Power Engineering applications (ICPEA) - Shaping Sustainability Through Power Engineering Innovation

作者： Ishak, Nurul Huda Binti Isa, Iza Sazanita Binti bin Osman, Muhammad Khusairi Daud, Kamarulazhar bin Jadin, Mohd Shawal Univ Teknol MARA Ctr Elect Engn Studies Permatang Pauh 13500 Pulau Pinang Malaysia Univ Malaysia Pahang Fac Elect & Elect Engn Technol Pekan 26600 Pahang Malaysia

ISBN: (纸本)9781665475013

Research in solar energy has rapidly grown since its significant and contributes to the advancement in clean renewable energy technology. Effective energy management such as fault detection impacts the early-stage monitoring for the efficiency, reliability, and safety of solar photovoltaic (PV) systems. The formation of a hotspot is one of the issues commonly occurred in a PV system. However, the main limitation of hotspot detection is the difficulty to interpret specific components with erratic temperatures in the thermographic images for attributes in the intelligence detection model. In this study, a review of hotspot detection in solar PV panels using the image processing method is established based on the image processing field. The integration of image processing approach can further assist in developing automated fault detection in solar PV farms for effective preventive monitoring methods. Therefore, several aspects need to be categorized and considered accordingly for achieving accurate prediction. Several ways were discussed, and future research is suggested in this study.

关键词： hotspot solar PV system image processing

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Circulation of Transformed image Derivatives with Parameterized Aliasing in the Off-Chain Storage

Circulation of Transformed Image Derivatives with Parameteri...

引用

ieee international conference on Consumer Electronics (ICCE)

作者： Yoshikawa, Ayano Matsubara, Katsuya Future Univ Hakodate Hakodate Japan

ISBN: (纸本)9781665491303

In major NFT marketplaces, digital image contents such as illustrations and photographs generally reside off-chain due to cost, performance, and privacy concerns. InterPlanetary File System (IPFS), a decentralized storage system, is widely used to store and distribute off-chain data of NFT artworks. applications of digital images generally require displaying, printing, and redistributing them in a variety of sizes, colors, and formats. Unfortunately, the content addressing in IPFS impedes reusing transformation results derived from an original image since totally different IDs from the original must be given for them. They can never comprehend any relation and transition between the original and derivatives. We introduce on-demand image transform functionality and cooperated ID aliasing capability into IPFS for identifying images generated through a transform with a combination of an original's ID and parameters of the applied transform. Our implementation allows retrieving results of newly demanded transforms by inquiring about corresponding IDs for the aliases to others. A preliminary experimental result demonstrates that the proposed ID aliasing can mitigate the processing overhead by promoting reclaiming of transformed images.

关键词： NFT IPFS image processing

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Maturity Level Detection of Banana Fruit by image processing Technique 8

Maturity Level Detection of Banana Fruit by Image Processing...

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8th international conference on computers and Devices for Communication, CODEC 2023

作者： Maity, Indranil Kashyap, Manas Sarkar, Moubani Kumar, Rohan West Bengal Kolkata India Kolkata UEM Department of Electronics and Communication Engineering West Bengal Kolkata India

ISBN: (纸本)9798350317176

The assessment of fruit ripeness is a critical task in various agricultural and food processing applications. Traditional methods of ripeness evaluation, which relied on human judgment, were subjective and labor-intensive. In this paper, a comprehensive approach is presented for fruit ripeness detection of banana using image processing technique. An algorithm was developed in MATLAB for finding different image components of banana sample and fundamental parameters like the number of yellow and white pixels. © 2023 ieee.

关键词： image processing

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