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检索条件"任意字段=2nd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2022"

共 88 条记录，以下是11-20 订阅

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ECT image reconstruction based on improved multi-scale residual network 2

ECT image reconstruction based on improved multi-scale resid...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Ma, Min Wu, Huan Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9781510660571

In order to solve the soft field effect in capacitance tomography lead to the problem of low quality of image reconstruction, this paper proposes an image reconstruction algorithm based on improved multi-scale residual network(IMRN), by introducing a multi-scale convolution structure layer information, abundant feature extracting multi-scale empty convolution structure, and then build a change with different expansion rate convolution receptive field, The global feature information is obtained and the number of network parameters is effectively reduced. The channel attention mechanism is used to weight the extracted features adaptively and filter the redundant information. Finally, the shallow features and the extracted features of each structure are fused to compensate the lost feature information. Simulation results show that compared with LBP algorithm, Landweber iterative algorithm and 1DCNN algorithm, the improved algorithm effectively improves the quality of image reconstruction. © 2022 SPIE.

关键词： Convolution

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image Recognition Model of Contour Extraction and Shape Recognition Based on Multiple Fusion algorithms 2

Image Recognition Model of Contour Extraction and Shape Reco...

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2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Xu, Song Xu, Changjie Tong, Lihong Wan, Qiwei Ding, Haibin State Key Laboratory of Performance Monitoring and Guarantee of Rail Transportation Infrastructure Jiangxi Nanchang330013 China Institute of Geotechnical Engineering School of Civil Engineering and Architecture East China Jiaotong University Jiangxi Nanchang330013 China

ISBN: (纸本)9781510660571

As the basic part of the field of image recognition, image edge contour extraction technology is facing more and more challenges with the deepening of image recognition technology in daily life. Based on multi-operator fusion ecological expansion method, an image edge extraction algorithm was proposed in this paper. The hybrid algorithm can eliminate the influence of some unfavourable conditions such as background noise, illumination reflective noise and extract the edge contours of single or multiple objects more accurately. According to the geometric characteristics of lines and arcs, we summarized and put forward a general method for judging whether a point sequence is a straight line or an arc, and a problem is solved based on this method, which proves the superiority of this method in the classification of contour types. Combined the existing research results and practical experience, we summarized a set of sub-pixel interpolation methods with high precision, high efficiency, and high feasibility. © 2022 SPIE.

关键词： image fusion

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Research and design of image super-resolution algorithm based on attention mechanism 2

Research and design of image super-resolution algorithm base...

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2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Tang, Yu Wang, Zi-Yi College of Computer and Information Science Chongqing Chongqing Normal University Chongqing China

ISBN: (纸本)9781510660571

image super-resolution algorithm is a technology that changes the image from low-resolution to high-resolution. It is widely used in various fields, including but not limited to image compression technology, satellite remote sensing imaging, urban traffic monitoring, medical imaging and so on. At present, the method based on deep learning has a very good effect on the super-resolution processing of low-resolution images, but some algorithms still have some problems, such as the loss of detail texture of the reconstructed image, and the large gap between the reconstruction results and the computational resources. To solve the above problems, this paper proposes a network model based on channel attention mechanism. The network model consists of three parts: the first part is a shallow feature extraction block, which is composed of a convolution layer and an activation layer, which is mainly used to extract the low-level features of the input image;The second part is the deep extraction block based on the channel attention mechanism, and the depth separable convolution is added to the local residual block of this part to effectively reduce the huge parameters generated by training. This module mainly extracts the high-level features of the input image;The third part is the reconstruction module, which is used to fuse the original image features extracted from the previous two parts and output the reconstructed image. Finally, the experimental results show that using this method will effectively improve the peak signal-to-noise ratio and structural similarity index of the reconstructed image. © 2022 SPIE.

关键词： Convolution

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Automatic Segmentation of Thyroid Nodule from Ultrasound images using Spatial-Channel Attentive U-Net 2

Automatic Segmentation of Thyroid Nodule from Ultrasound Ima...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Song, Shuang Liu, Linlin Yu, Ming-An Xiao, Ruoxiu School of Computer Science and Engineering Beihang University Beijing100091 China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Department of Interventional Medicine China-Japan Friendship Hospital Beijing100029 China Shunde Graduate School University of Science and Technology Foshan Beijing100024 China

ISBN: (纸本)9781510660571

The ultrasound image is a commonly used imaging modality to treat thyroid nodules due to its rapid imaging speed and the ability for multiple anatomical and soft-tissue visualization. However, considering the variability of the position, shape, size and intensity of nodules, the accurate segmentation of thyroid nodules is challenging. In this paper, we proposed an automatic segmentation network of thyroid nodules by combining fast-RCNN and spatial-channel attentive U-Net. In our model, fast-RCNN is firstly utilized to identify the rough position of nodules. The predicted boxes are then utilized to crop the image patches containing only nodules and then build a new database. Next, a spatial-channel attentive U-Net is designed and trained to realize the nodule segmentation. By comparing the proposed network with other state-of-the-art models, we can gain superior results in discarding similar non-nodule structures and preserving the boundary information of nodules. © 2022 SPIE.

关键词： image segmentation

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A feature extraction with pose-auxiliary method for Person Reidentification 2

A feature extraction with pose-auxiliary method for Person R...

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2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Ma, ZePing Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu610054 China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China

ISBN: (纸本)9781510660571

Person re-identification is widely considered as a sub problem of image retrieval. It is a technology that uses computer vision technology to determine whether there is a specific pedestrian in an image or video, given a monitored pedestrian image, the pedestrian image under the cross device is retrieved. Many researches have been made to study how to match one people from two picture, but how to locating proper body parts has become a problem which could lead to misalign and wrongly divided sample. To solve this problem, we introduce a pose-auxiliary network to extract the position feature of pedestrian. We use a post estimation network to estimate the person's body location, then we decide whether it's a body part or a static obstacle by using a separated trained classifier. Then we compare these features from two picture and calculate their loss. Meanwhile, we use a graph-matching strategy to compare two pedestrians pose structure, which is also used into jugging the match problem. By using a multi-verification strategy, our method has some improvement than some previous study using Market-1501 and DukeMTMC-Reid datasets, but still remains room for improvement. © 2022 SPIE.

关键词： image retrieval

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Software Application for Simulation-Based AES, RSA and Elliptic-Curve algorithms 2

Software Application for Simulation-Based AES, RSA and Ellip...

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2nd international conference on advanced Technologies for signal and image processing (ATSIP)

作者： Chaouch, Asma Bouallegue, Begacem Bouraoui, Ouni Fac Sci Monastir Lab Elect & Microelect E E Monastir 5000 Tunisia

ISBN: (纸本)9781467385268

In this paper we represent a developing work in an advanced algorithm for image encryption. First, we have programmed a flexible encrypting algorithms based on AES, RSA and elliptic-curves methods for text encrypting. Second, we have integrated this algorithms to encrypt compressed images. Finally we have provided a fair comparison between the three most famous encryption algorithms: AES, RSA and ellicptic curves. Since the objective here is the efficacy of the algorithms under different settings, the behavior and the performance are taken into consideration in this study comparison of the algorithm when different data loads are used. The presented comparison is based on these parameters: key size, block size and speed. The software application is implemented using C programming.

关键词： Encryption image AES RSA ECC

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Research on algorithms of Computer image Intelligent Recognition and Deep Learning 2

Research on Algorithms of Computer Image Intelligent Recogni...

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2nd international conference on signal image processing and Communication, ICSIPC 2022

作者： Shao, Zheneenji Zhou, Jingxuan Sichuan University Chengdu China Dalian University of Technology Dalian China

ISBN: (纸本)9781510657694

In recent years, with the rapid development of science and technology in my country, people's requirements for computer information technology have become higher and higher. In order to better explore new things, engineers and technicians need to continuously optimize computer information processing systems to help people better solve practical problems. The article mainly analyzes the development process of computer intelligent image recognition algorithms, expounds the computer intelligent image recognition algorithm, and finally puts forward the technical application of computer intelligent image recognition algorithm, which provides a certain research foundation for related staff. © 2022 SPIE.

关键词： image recognition

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Design and research of image processing art design system 2

Design and research of image processing art design system

引用

2022 2nd international conference on Artificial Intelligence, Big Data and algorithms, CAIBDA 2022

作者： Wang, Weiwei Science and Technology College Gannan Normal University Jiangxi Ganzhou341000 China

ISBN: (纸本)9783800760268

Because the image quality processed in the traditional art design system can not meet the requirements, so it is necessary to solve this problem to improve the intelligence of the art design *** the art design system, establish a perfect system architecture, and study each template. The image processing technology is more commonly used in edge detection, so it is necessary to use the zero crossover operator, Robert operator and Gaussian Laplace operator to realize edge detection. After the final system performance test can also prove that the intelligence of the image processing art design system has been effectively improved. It not only improves the quality of the image, but also improves the signal to noise ratio of the image. However, in the subsequent research, the theme is to strengthen the stability and safety of the system. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Edge detection

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Auto thresholds of image multi-level segmentation applying maximum value to construct 2 d histogram 4

Auto thresholds of image multi-level segmentation applying m...

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4th international conference on advanced algorithms and signal image processing, aasip 2024

作者： Zhang, Yunfei Zhang, Zhan Xu, Ri Wang, Ping He, Xianghong College of General Education Guangdong University of Science and Technology Guangdong Dongguan523083 China Co. Ltd. Xicheng District Beijing10020 China Department of Planning and Development Avic Composite Corporation Ltd. Aviation Industrial Park Shunyi District Beijing100300 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

It may achieve auto segmentation to construct 2 D histogram utilizing 2 D entropy. Habitual approach practices center gray scale and average scale of points in the same 4 neighbor. Actually, the horizontal or vertical change of the gray scale will not stand for the whole natures among neighbor points also. A maximum value way is constructed to established 2 D histogram by utilizing of center gray value and maximum value of 4 other point gray values except 4 neighbor points in the same 3×3 neighbor. The effects of multi-level experiments to almost all images in Matlab image toolbox manifest the validity of the constructed way. © 2024 SPIE.

关键词： image segmentation

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Analysis of mini program user usage market based on decision tree classification and decision tree regression algorithm 4

Analysis of mini program user usage market based on decision...

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4th international conference on advanced algorithms and signal image processing, aasip 2024

作者： Liu, Lidong Huang, Rui Li, Xiaoqin Luo, Yongbin Zhang, Rong Department of Computer Science Guangdong University of Science and Technology No. 2 Songshan Lake Section Dongguan523083 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

The decision tree classification algorithm identifies category patterns in data by constructing a tree like structure, while the decision tree regression algorithm predicts the trend of continuous numerical changes based on the tree model. This article uses decision tree classification and decision tree regression algorithms to analyze the market for mini program users. Through classification algorithms, we have gained a profound insight into the activity classification characteristics of mini program users at different time periods. These analyses not only reveal the evolution trajectory of user behavior patterns, but also provide us with an advanced perspective to understand market dynamics. At the same time, regression algorithms, with their precise predictive ability, accurately depict the growth and decline of the market size used by mini programs, injecting strong momentum into predicting market trends. This comprehensive analysis method that integrates classification and regression algorithms endows mini program developers with the super ability to insight into user activity in the time dimension, thereby helping them formulate strategies more accurately and efficiently, and promoting the stable and sustainable growth of mini program user scale. © 2024 SPIE.

关键词： Random forests

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