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International Conference on Information Sciences,Machinery,Materials and Energy（ICISMME 2015）

作者： Xiaoling LI Jimin YUAN School of Computer Science and Technology Chengdu University University Key Laboratory of Pattern Recognition and Intelligent information Processing The Department Computer Engineering Chengdu Aeronautic Vocational and Technical College

In view of the draw backs of apple grade identification in China,which still relies on photoelectric sorting and manual separation,this paper presents a processing method on the basis of the technology of computer vision and digital *** image processing technology,the researcher calculated the length of the long-short-axis,marked the location of it and calculated the 4 parameters,color,mean square,shape,size,as the key characteristics of the BP input of network to build a network and identify the level of apple through analysis of the external characteristics of *** optimum structure parameters of the BP neural network which had 9 hidden layer neurons were determined by RP training *** showed that average accuracy for fruit classification can reach 92.5% by using this model,and the executing time of microcomputer for grading of one apple is 9.3 *** method has the characteristics of high accuracy and good real-time performance.

关键词： characteristic parameter BP neural network apple detect level

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An effective document image deblurring algorithm

An effective document image deblurring algorithm

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Conference on Computer Vision and pattern recognition (CVPR)

作者： Xiaogang Chen Xiangjian He Jie Yang Qiang Wu Key Laboratory of System Control and Information Processing Ministry of Education China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Centre of Innovation in IT Services and Applications University of Technology Sydney Australia

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method.

关键词： Image restoration Histograms TV Object segmentation Deconvolution Estimation Image segmentation

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Isoform Function Prediction Based on Heterogeneous Graph Attention Networks

Isoform Function Prediction Based on Heterogeneous Graph Att...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Guo, Kuo Li, Yifan Chen, Hao Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Institute of Image Processing and Pattern Recognition Shanghai200240 China Carnegie Mellon University School of Computer Science Computational Biology Department PittsburghPA15213 United States

ISBN: (纸本)9798350337488

Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bioinformatics as it can provide valuable insights into the intricate mechanisms of gene regulation and biological processes. Conventionally, gene function labels are standardized in Gene Ontology (GO) terms. However, traditional methods for predicting isoform function are largely limited by the absence of isoform-specific labels, sparse annotations, and the vast number of GO terms. To address these issues, we propose HANIso, a deep learning-based method for isoform function prediction. HANIso leverages a pretrained protein language model to extract features from protein sequences. It also integrates heterogeneous information, such as isoform sequence features, GO annotations, and isoform interaction data, using a Heterogeneous Graph Attention Network (HAN). This allows the model to learn the importance of different sources of information and their semantic relationships through the attention mechanism. Our method can predict function labels at both the gene level and isoform level. We conduct experiments on two species datasets, and the results demonstrate that our method outperforms existing methods on both AUROC and AUPRC. HANIso has the potential to overcome the limitations of traditional methods and provide a more accurate and comprehensive understanding of isoform function. © 2023 IEEE.

关键词： alternative splicing gene ontology heterogeneous graph attention network isoform function prediction protein language model

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Improved global optical flow estimation with mean shift algorithm for target detection

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International Journal of Wireless and Mobile Computing 2015年第4期8卷 323-328页

作者： Wang, Zhonghua Li, Chunyong Liu, Qingping Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang Jiangxi Province330063 China School of Information and Engineering Nanchang Hangkong University Nanchang Jiangxi Province330063 China

In view of the problem that the global optical flow algorithm cannot acquire accurate motion parameter estimation at a low-gradient value, an improved method has been presented in order to enhance the self-adaptive ability. The proposed method is divided into three steps: firstly, the Gaussian filter is used to restrain the background noise;secondly, the optical basic constraint weighted function is modified to acquire targets area;finally, the morphological filtering and mean shift segmentation algorithm is adopted to reduce the false alarm rate. Compared with other algorithms, the experiment results show that the proposed method can improve the self-adaptive ability and the detection rate. © 2015 Inderscience Enterprises Ltd.

关键词： Optical flows

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SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical Image Segmentation 1

SliceProp: A Slice-Wise Bidirectional Propagation Model for ...

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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Xu, Xin Lu, Wenjing Lei, Jiahao Qiu, Peng Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Vascular Surgery China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9798350358780

Interactive medical image segmentation methods have become increasingly popular in recent years. These methods combine manual labeling and automatic segmentation, reducing the workload of annotation while maintaining high accuracy. However, most current interactive segmentation frameworks are limited to 2D image data, and are not suitable for 3D image data due to the large size and high complexity of 3D data, as well as the challenges posed by information asymmetry and sparse annotation. In this paper, we propose SliceProp, an interactive segmentation framework that implements slice-wise Label Bidirectional Propagation (LBP) for 3D medical image segmentation. SliceProp extends the interactive 2D image segmentation algorithm to 3D image segmentation, and can handle 3D data with large size and high complexity. Moreover, equipped with a Backtracking Feedback Check (BFC) module, SliceProp effectively addresses the issues of information asymmetry and spatial sparse annotation in 3D medical image segmentation. Additionally, we adopt an uncertainty-based criterion to pri-oritize the slices to be refined interactively, which enhances the efficiency of the interaction process by enabling the model to focus on the regions with the most unreliable predictions. SliceProp is evaluated on two datasets and achieves promising results compared to state-of-the-art methods. © 2023 IEEE.

关键词： Medical imaging

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Object based video watermarking scheme using inertia ellipse and shape adaptive DCT

Object based video watermarking scheme using inertia ellipse...

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IEEE Workshop on Multimedia Signal processing

作者： Guo Jie Shi Peng-fei Fang Tao Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China The State Key Laboratory of Information Security Chinese Academy and Sciences Beijing China Chinese Academy of Seiencer The State Key Laboratory of Information Security Beijing China

ISBN: (纸本)0780377133

Video object (VO) is an important concept in MPEG-4. For objects can be easily manipulated without visible distortion, the copyright protection of video objects becomes an important issue. This paper presents a watermarking scheme for video objects. Different from other methods, the proposed scheme employed inertia ellipse to achieve fast synchronization recovery in case the object was manipulated. Shape adaptive DCT and visual mask were combined to embed the watermark into the arbitrarily shaped object, which was designed to achieve the trade-off between the invisibility and the robustness. Experiments show that our algorithm is robust to object manipulations such as rotations, translations, scaling and lossy compression. Our scheme can be easily incorporated into the object-based coding framework of MPEG-4.

关键词： Watermarking Shape Discrete cosine transforms MPEG 4 Standard Robustness Image coding Streaming media Discrete wavelet transforms Image processing Image recognition

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QT-based monitoring system of multi-functional laboratory

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Research Journal of Applied Sciences, Engineering and Technology 2012年第21期4卷 4480-4483页

作者： Xiaoling, Li Jimin, Yuan School of Computer Science and Technology Chengdu University Chengdu 610106 China Key University Key Laboratory of Pattern Recognition and Intelligent information Processing Sichuan Province China School of Computer Science and Technology Panzhihua University Panzhihua 617000 China

Regarding the embedded processor as the core, this study utilizes various cutting-edge technologies such as wireless LAN, USB interface, Bluetooth, multimedia, etc., to propose the design program of QT-based security monitoring system. Taking the lab environment in school as an example, this system has achieved the security monitoring, information transmission and control of certain equipment. Besides, it has cut the Linux kernel module reasonably and explored the touch screen, serial port, wireless LAN, Bluetooth, USB and other resources, thus realizing various functions, such as collection and processing of audio, video and security information and wireless communication. Thereby, users can carry out real-time monitoring for multiple locations through the wireless LAN. © Maxwell Scientific Organization, 2012.

关键词： Bluetooth

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Semantic Transformation-Based Data Augmentation for Few-Shot Learning

SSRN

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SSRN 2023年

作者： Pan, Mei-Hong Xin, Hong-Yi Shen, Hong-Bin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Jiaotong University Shanghai200240 China

Few-shot learning (FSL) as a data-scarce method, aims to recognize instances of unseen classes solely based on very few examples. However, the model can easily become overfitted due to the biased distribution formed with extremely limited training data. This paper presents a task specific data augmentation approach by transferring samples from base dataset to the novel tasks in an encoder-decoder paradigm, which guarantees generating semantically meaningful features. Specifically, the feature transfer process is carried out in semantic space. We further impose a compactness constraint to the generated features with the prototypes working as the reference points, which ensures the generated features distribute around the class centers. Moreover, we incorporate the cluster centers of the query set with the prototypes of the support set to reduce the bias of the class centers. With the supervision of the compactness loss, the model is encouraged to generate discriminative features with high inter-class dispersion and intra-class compactness. Extensive experiments show that our method outperforms the state-of-the-arts on four benchmarks, namely MiniImageNet, TieredImageNet, CUB and CIFAR-FS. © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Multiscale centerline extraction of angiogram vessels using gabor filters

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3314卷 570-575页

作者： Sang, Nong Tang, Qiling Liu, Xiaoxiao Weng, Wenjie Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

In this paper, we propose a new automated approach to extract the centerlines from 2-D angiography. The centerline extraction is the basis of 3-D reconstruction of the blood vessels, so the accurate localization of centerlines counts for much. The characteristics of multiscale Gabor even filter, flexible frequency bands and enhancement effects, are fully utilized to detect centerlines of the blood vessels in various size. © Springer-Verlag 2004.

关键词： Blood vessels

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A DSP/FPGA - Based Parallel Architecture for Real-time Image processing

A DSP/FPGA - Based Parallel Architecture for Real-time Image...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Luxin Yan Tianxu Zhang Sheng Zhong Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A DSP/FPGA-based parallel architecture oriented to real-time image processing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high image processing performance, which achieve a good balance for parallel image processing

关键词： Digital signal processing Field programmable gate arrays Parallel architectures Image processing Data communication Computer architecture Multiprocessor interconnection networks Protocols Performance evaluation Prototypes

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