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GAU-Nets: Graph Attention U-Nets for image Classification 5

GAU-Nets: Graph Attention U-Nets for Image Classification

引用

2021 5th international Workshop on advanced algorithms and Control Engineering, IWAACE 2021

作者： Zhao, Haoran Zhang, Chengwei School of Artificial Intelligence Hebei University of Technology Tianjin300132 China

Graph neural network is a research hotspot in the field of deep learning recently, and its application has become more and more extensive. A new graph neural network model is proposed, Graph Attention U-Nets(GAU-Nets for short), which has strong processing capabilities for graph structures. In GAU-Nets, the graph data structure is preliminarily processed through GCN, and then extracted the features by the graph pooling and Unpooling blocks. We innovatively added the attention mechanism to GAU-Nets to avoid forgetting the important information. We have done a lot of image classification experiments on MS-COCO and other datasets. The experimental results prove that GAU-Nets performs better than other traditional graph neural network models. Without bells and whistles, our GAU-Nets method has an accuracy of 69.1% on the MS-COCO data set and 82.1% on the VOC 2007 data set, which has surpassed all benchmark methods. © Published under licence by IOP Publishing Ltd.

关键词： image classification

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MRR-UNet: Skin Lesion image Segmentation Based on Mixed Receptive Field Residual Convolutional Neural Network 8

MRR-UNet: Skin Lesion Image Segmentation Based on Mixed Rece...

引用

8th international conference on Communication, image and signal processing, CCISP 2023

作者： Liu, Yun Chen, Ji Wang, Xing School of Information Science and Engineering Linyi University Linyi China

ISBN: (纸本)9798350305838

Medical image segmentation is a fundamental work in computer-aided medicine. The accuracy of segmentation results has an important impact on lesion-assisted analysis. algorithms for segmentation of skin lesion image based on deep learning are significant for clinical diagnosis. However, these methods have the following challenges in extracting regions of interest: (1) The intra-class variability of different medical images is ignored. (2) Insufficient extraction of local information due to fixed-size convolutional kernel. In order to cope with these challenges, this paper presents a novel skin lesion image segmentation approach utilizing Mixed Receptive Field Residual Convolutional Neural Network as its foundation. In this paper, a Mixed Receptive Field Residual Module (MRRM) is designed to achieve better capture of multi-scale feature information. By utilizing Dilated Convolution and Depthwise Convolution with multiple sizes of convolution kernels, the proposed method achieves the capability to extract contextual semantic information within the field of view. And the residual structure enables better utilisation and reuse of low-level feature information. The proposed method achieves impressive results on ISIC2018 dataset, with an IoU metric of 83.42% and a Dice coefficient of 90.57%. © 2023 IEEE.

关键词： Convolution

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Wind Field Inversion and Reconstruction Based on ADS-B Data 3

Wind Field Inversion and Reconstruction Based on ADS-B Data

引用

3rd IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2021

作者： Xiaoyun, Shen Zixuan, Zhao Siyuan, Zhang Weidong, Jiao Chong, Ma Tianying, Wang Tianjin Key Lab for Advanced Signal and Image Processing Civil Aviation University of China Tianjin China

ISBN: (纸本)9781665425186

To accurately perceive sudden airflow changes during flight and avoid aviation safety risks caused by sudden weather at high altitudes, it is necessary to invert and reconstruct the wind field during flight. Based on the random sample consensus estimation, the improved Least Squares algorithm is used to fit the Automatic Dependent Surveillance-Broadcast (ADS-B) data. Firstly, the vertical wind profile is constructed by inverting the wind vectors at different altitude levels at the fixed airport location and compared with the meteorological data of the European Center for Medium-Range Weather Forecasts (ECMWF) to verify the feasibility and accuracy of the algorithm. Then, the wind field under the complete track of a specific flight is reconstructed to obtain the wind field distribution along the route. Finally, regional wind fields at different altitudes are reconstructed using multiaircraft data in a fixed range. The experimental results show that this method can better reflect the real complex wind field structure. © 2021 IEEE

关键词： Weather forecasting

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Robust JPEG image Steganography Using Wavelet Domain SVD and Adaptive QIM 8

Robust JPEG Image Steganography Using Wavelet Domain SVD and...

引用

8th international conference on signal and image processing, ICSIP 2023

作者： Liu, Jing Song, Xiaofeng Li, Guopeng Han, Kun Xi'An University of Posts & Telecommunications Information Network Center Xi'an710121 China National University of Defense Technology Test Center Xi'an710106 China

ISBN: (纸本)9798350397932

Massive images in Internet networks provides rich cover objects for covert communication using digital steganography. However, the lossy processing such as image compressing and image scaling often take place in some network platforms, which makes the existing image steganography algorithms designed for lossless environment unusable for lossy network platforms. Based on singular value decomposition (SVD) in stationary wavelet domain, a robust and adaptive image steganography algorithm is proposed, which can resist lossy image compression and extract the embedded secret message correctly. First, stationary wavelet transformation is performed for cover image, and the low-frequency subband is divided into non-overlapping blocks, and SVD is performed for each block;second, considering the stability of maximum singular value, the cover elements are extracted by applying a adaptive quantization index modulation (QIM) process on the maximum singular values;third, the embedding distortion function is defined according to the influence of the cover element change on the inter-block and intra-block wavelet coefficients, and the secret messages are embedded using syndrome-trellis code (STCs);finally, the adaptive QIM is used to embed the secret elements and generate the stego image. The experimental results show that the proposed steganography algorithm has better robustness and stronger anti-detection capabilities. © 2023 IEEE.

关键词： Singular value decomposition

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Magic Mirror Stealth: Interactive Automatic Picture Editing System 18th

Magic Mirror Stealth: Interactive Automatic Picture Editing ...

引用

18th Pacific Rim international conference on Artificial Intelligence, PRICAI 2021

作者： Zhou, MengDi Hu, BoHeng Liu, Si Institute of Information Engineering Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Beijing No. 8 High School Beijing China BeiHang University Beijing China

ISBN: (纸本)9783030891879

This paper builds an interactive automatic picture editing system based on the most advanced algorithms in the field of multi-modality. It removes a specific area or entity in the image according to the natural language expression, which is like a magic mirror that can make the target invisible. The system is composed of two core processing modules: a referring image segmentation module based on natural language expressions and an automatic image inpainting module. The two modules cooperate to precisely control the editing area and generate the editing results based on the image semantics, which can ensure that the edited images are natural, realistic, and meet the editing needs of users. The two modules of the system are trained on open-source datasets separately. Experimental results demonstrate that the system can help users quickly edit images by a natural language expression. © 2021, Springer Nature Switzerland AG.

关键词： image segmentation

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image Decomposition Based on Region-Constrained Smoothing 25th

Image Decomposition Based on Region-Constrained Smoothing

引用

25th international conference on Pattern Recognition Workshops, ICPR 2020

作者： Chochia, Pavel A. Institute for Information Transmission Problems Russian Academy of Sciences Bolshoy Karetny per. 19 Moscow127051 Russia

ISBN: (纸本)9783030688202

The task of image decomposition is to split an image into piecewise smooth structural and difference texture-noise components. It is used in many tasks of video information processing and analyzing. The problem of decomposition is to provide independent smoothing in each of the structural regions of the image and to preserve the signal structure. Most of the known methods of decomposition and smoothing are based on analysis of measurable parameters of the local image area, for example, the distribution of signal values. These data does not reflect image area characteristics well enough. Obvious criterion for spatial limiting of the analyzed area is the belonging of the target and surrounding points to the same image spatial area. A sufficient criterion for the connectivity of the points in a region is the absence of contour edges between them. The article proposes an approach to the construction of a decomposition algorithm based on a preliminary delineation of image areas by detecting contours between them and subsequent contour-limited smoothing inside each of the areas. The concept of similarity of points in the image is introduced, on the basis of which the smoothing algorithm is built. Experimental comparisons of the proposed algorithm with other well-known smoothing algorithms are carried out. © 2021, Springer Nature Switzerland AG.

关键词： image analysis

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A Remote Sensing image Object Detection Algorithm Based on a Fusion of Classification and Regression Branches 8

A Remote Sensing Image Object Detection Algorithm Based on a...

引用

8th international conference on signal and image processing, ICSIP 2023

作者： Li, Zejun Zhou, Danshu Liu, Jian Wu, Nanjian Liu, Liyuan Dou, Runjiang University of Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering Beijing100049 China Institute of Semiconductors State Key Laboratory of Superlattices and Microstructures Chinese Academy of Sciences Beijing100083 China University of Chinese Academy of Sciences College of Integrated Circuits Beijing100049 China

ISBN: (纸本)9798350397932

The detection head of most object detection algorithms obtains the category information and location information through classification branch and regression branch, respectively. Usually, the two branches do not influence each other, therefore neither the positional information implied in the classification branch, nor the classification information implied in the regression branch is used. In this paper, we redesign the traditional detection head to solve the above problems. The mAP of our method in the public remote sensing image object detection dataset DOTA-v1.0 reaches 77.27%, while the mAP of baseline (RoI Transformer) is only 75.43% under the same training conditions. The test results suggest that the detection head branch fusion algorithm can improve the performance of the remote sensing image object detection model. © 2023 IEEE.

关键词： Classification (of information)

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Overview of SAR image Denoising Based on Transform Domain 1

引用

2nd international conference on 3D Imaging Technologies-Multidimensional signal processing and Deep Learning, 3DIT-MSPandDL 2020

作者： Sun, Yu Xin, Zhihui Huang, Xiaoqiao Wang, Zhixu Xuan, Jiayu Yunnan Key Lab of Opto-Electronic Information Technology Yunnan Normal University Kunming China

ISBN: (数字)9789811633911

ISBN: (纸本)9789811633904

Synthetic aperture radar (SAR) image denoising processing is a particularly important issue. This paper mainly discusses SAR image denoising based on the transform domain. First, this paper describes the formation mechanism of coherent speckle noise and the basic methods of suppressing coherent speckle. Then, the denoising algorithms based on wavelet transform and multi-scale analysis are introduced, respectively. The representative algorithms are verified by simulation. Finally, the paper summarizes the advantages and disadvantages of existing algorithms, and proposes the development trend of SAR image denoising in transform domain. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wavelet transforms

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image processing Based on Inter-frame Color Feature Matching for Visible Light Positioning 2

Image Processing Based on Inter-frame Color Feature Matching...

引用

2nd international conference on signal processing and Intelligent Computing, SPIC 2024

作者： Yu, Baozhu Liu, Xiangyu Chen, Yaoheng Guo, Lei Bao, Jianbo Sun, Jiandong Shenyang Ligong University School of Information Science and Engineering Shenyang China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China Chongqing University of Posts and Telecommunications School of Communication and Information Engineering Chongqing China Nari Group Corporation State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350368888

The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the high complexity of traditional image processing algorithms, existing VLP systems are unable to provide real-time positioning services. In response to the above issue, we propose an image processing mechanism based on the inter-frame color feature matching method, which includes the equidistant sampling processing, low complexity decoding algorithm, and color feature matching-based LED region of interest (ROI) determination method. The results show that the system average positioning delay is 80.2ms, indicating better system real-time performance. © 2024 IEEE.

关键词： Color image processing

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Multi-Source Remote Sensing image Registration Method Based on Nonlinear Scale Space and Phase Congruency 2

Multi-Source Remote Sensing Image Registration Method Based ...

引用

2nd IEEE international conference on signal, Information and Data processing, ICSIDP 2024

作者： Chen, Yuejuan Li, Xianglei Huang, Pingping Tan, Weixian Li, Xiujuan Yin, Bo Inner Mongolia University of Technology Mongolia Key Laboratory of Radar Technology and Application College of Information Engineering Hohhot China Inner Mongolia University of Technology Mongolia Key Laboratory of Radar Technology and Application College of Resources and Environmental Engineering Hohhot China

ISBN: (纸本)9798331515669

Due to differences in sensor characteristics, imaging conditions, and time among multi-source remote sensing images, nonlinear changes in image radiance intensity occur, increasing the difficulty of image registration. Existing techniques often face challenges in the robustness and accuracy of feature matching when addressing these nonlinear radiance variations. To solve this problem, this paper proposes a phase congruency remote sensing image registration method based on nonlinear scale space. This method constructs a nonlinear scale space of the image using an improved anisotropic diffusion filter, effectively suppressing noise while preserving the edges and detailed features of the image. It calculates the edge strength and corner strength of the image at different scales using a phase congruency model and extracts feature points from the edge strength map and corner strength map. Multi-scale, multi-direction descriptors are constructed using the response values generated by the Log-Gabor filter to enhance the robustness of feature extraction, thereby achieving precise registration of multi-source remote sensing images. Experimental results show that this method significantly suppresses image noise and nonlinear radiance differences, and outperforms traditional algorithms and other improved registration algorithms regarding the number of correctly matched point pairs and robustness. © 2024 IEEE.

关键词： Gabor filters

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