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learning-based parameter prediction for quality control in three-dimensional medical image compression

Frontiers of Information Technology & Electronic Engineering 2021年第9期22卷 1169-1178页

作者： Yuxuan HOU Zhong REN Yubo TAO Wei CHEN State Key Lab of CAD&CG Zhejiang UniversityHangzhou 310058China The First Affiliated Hospital Zhejiang UniversityHangzhou 310003China

Quality control is of vital importance in compressing three-dimensional(3D)medical imaging *** com-pression parameters need to be determined based on the specific quality *** high efficiency video coding(HEVC),regarded as the state-of-the-art compression tool,the quantization parameter(QP)plays a dominant role in controlling *** direct application of a video-based scheme in predicting the ideal parameters for 3D medical image compression cannot guarantee satisfactory *** this paper we propose a learning-based parameter prediction scheme to achieve efficient quality *** kernel is a support vector regression(SVR)based learning model that is capable of predicting the optimal QP from both vid-eo-based and structural image features extracted directly from raw data,avoiding time-consuming processes such as pre-encoding and iteration,which are often needed in existing *** results on several datasets verify that our approach outperforms current video-based quality control methods.

关键词： Medical image compression High efficiency video coding(HEVC) Quality control learning-based

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Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi AL-MEKHLAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

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A Retrieval Matching Method based Case learning for 3D Model

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Journal of Software Engineering and Applications 2012年第7期5卷 467-471页

作者： Zhi Liu Qihua Chen Caihong Xu College of Computer Science and Technology Zhejiang University of Technology Hangzhou China

The similarity metric in traditional content based 3D model retrieval method mainly refers the distance metric algorithm used in 2D image retrieval. But this method will limit the matching breadth. This paper proposes a new retrieval matching method based on case learning to enlarge the retrieval matching scope. In this method, the shortest path in Graph theory is used to analyze the similarity how the nodes on the path between query model and matched model effect. Then, the label propagation method and k nearest-neighbor method based on case learning is studied and used to improve the retrieval efficiency based on the existing feature extraction.

关键词： Case learning-based Retrieval Matching Similarity Matching

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Survey on Spam Filtering Techniques

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Communications and Network 2011年第3期3卷 153-160页

作者： Saadat Nazirova 不详

In the recent years spam became as a big problem of Internet and electronic communication. There developed a lot of techniques to fight them. In this paper the overview of existing e-mail spam filtering methods is given. The classification, evaluation, and comparison of traditional and learning-based methods are provided. Some personal anti-spam products are tested and compared. The statement for new approach in spam filtering technique is considered.

关键词： E-mail Spam Unsolicited Bulk Messages Filtering Traditional Methods learning-based Methods Classification

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