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7th International Conference on Systems and Informatics, ICSAI 2021

作者： Li, Jie Yang, Jie Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai China

ISBN: (纸本)9781665426244

In view of the wide variety of plants on the earth, the plant species identification is particularly necessary to protect and preserve biodiversity. In this work, we propose a plant image classification method based on the encoder-decoder model with additive attention mechanism to extract plant image features and convert them into text descriptions related to plant features. In a well-trained network, it can successfully classify on the species of the generated plant texts. We show that, the proposed method not only equalizes the results of deep convolutional neural network on classification task, but also uses of the prior information of botanists in classification, and thus provide a significant prediction result. © 2021 IEEE.

关键词： image classification

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Dynamical model of traffic congestion with the consideration of the next-nearest-neighbor interaction

Dynamical model of traffic congestion with the consideration...

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6th World Congress on Intelligent Control and Automation, WCICA 2006

作者： Zhipeng, Li Xiaobo, Gong Yuncai, Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)1424403324

By introducing the velocity difference between the preceding car and the car before the preceding one into the optimal velocity model (OVM), we present an extended dynamical model which takes into account the next-nearest-neighbor interaction. The stability condition of this model is derived by considering a small perturbation around the uniform flow solution with finding that traffic congestion is suppressed efficiently by incorporating the effect of new consideration. Then we investigate the property of the model using numerical methods. The results indicate that the next-nearest-neighbor interaction has important impacts on the coexisting flow, the relation between flow and density, and the propagation speed of small disturbance (PSSD). In addition, we have a try to further enhance the stability of traffic flow by introducing the relative velocity of an arbitrary number of cars in front, but the analysis of linear stability shows it is poor for our purpose. © 2006 IEEE.

关键词： Traffic congestion

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Progressive low/high-resolution space attention fusion network for single image super-resolution

Progressive low/high-resolution space attention fusion netwo...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Zhong, Chengzu Zhou, Yue Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

The general single image super-resolution methods mainly extract features from the high-resolution (HR) space by the pre-upscaling step at the beginning of the network or from the low-resolution (LR) space before the post-upscaling step at the end of the network. The former way requires high computation as well as misleading the network by wrong artificial priors. The latter way cannot learn mapping well by only conducting simple operations in HR space. In this paper, we aim to utilize the features from LR and HR space more efficiently and propose the novel network, which applies a frequency-slicing mechanism to divide features into LR and HR space, a direction-aware fusion residual group to extract distinctive features in LR space and an attention fusion module to recalibrate features in HR space. The experimental results demonstrate that our model is superior to the state-of-the-art methods upon quantitative metrics and visual quality. © 2021 institute of Physics Publishing. All rights reserved.

关键词： Optical resolving power

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A new nonlinear interpolation algorithm for edge preserving

A new nonlinear interpolation algorithm for edge preserving

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International Conference on Multimedia Technology

作者： Wang, Fujian Xu, Yiren Zhao, Yuming Hu, Fuqiao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781424478743

This paper presents a new interpolation method for edge preserving when a low-resolution image is converted into a high-resolution image. The algorithm is based on both geometric closeness and photometric similarity, unlike the conventional interpolation algorithm which only uses geometric closeness. The proposed interpolation algorithm can preserve high frequencies in edge regions and retain similar conventional interpolation in smooth regions. The results of the proposed algorithm have higher peak signal-to-noise ratios (PSNR) and show a visual improvement with sharp edges compared to the conventional interpolation algorithm. ©2010 IEEE.

关键词： Interpolation

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A novel color image encryption algorithm based on genetic recombination and the four-dimensional memristive hyperchaotic system

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Chinese Physics B 2016年第10期25卷 76-88页

作者：柴秀丽甘志华路杨张苗辉陈怡然 School of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Department of Electrical and Computer Engineering University of Pittsburgh School of Software Henan University Research Department Henan University

Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them. In the paper, a novel color image encryption algorithm is introduced. The 24 bit planes of components R, G, and B of the color plain image are obtained and recombined into 4 compound bit planes, and this can make the three components affect each other. A four-dimensional(4D) memristive hyperchaotic system generates the pseudorandom key streams and its initial values come from the SHA 256 hash value of the color plain image. The compound bit planes and key streams are confused according to the principles of genetic recombination, then confusion and diffusion as a union are applied to the bit planes,and the color cipher image is obtained. Experimental results and security analyses demonstrate that the proposed algorithm is secure and effective so that it may be adopted for secure communication.

关键词： genetic recombination memristive hyperchaotic system color image encryption confusion diffusion

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LncLocator 2.0: A cell-line-specific subcellular localization predictor for long non-coding RNAs with interpretable deep learning

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Bioinformatics 2021年第16期37卷 2308-2316页

作者： Lin, Yang Pan, Xiaoyong Shen, Hong-Bin Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

Motivation: Long non-coding RNAs (lncRNAs) are generally expressed in a tissue-specific way, and subcellular localizations of lncRNAs depend on the tissues or cell lines that they are expressed. Previous computational methods for predicting subcellular localizations of lncRNAs do not take this characteristic into account, they train a unified machine learning model for pooled lncRNAs from all available cell lines. It is of importance to develop a cell-line-specific computational method to predict lncRNA locations in different cell lines. Results: In this study, we present an updated cell-line-specific predictor lncLocator 2.0, which trains an end-to-end deep model per cell line, for predicting lncRNA subcellular localization from sequences. We first construct benchmark datasets of lncRNA subcellular localizations for 15 cell lines. Then we learn word embeddings using natural language models, and these learned embeddings are fed into convolutional neural network, long short-term memory and multilayer perceptron to classify subcellular localizations. lncLocator 2.0 achieves varying effectiveness for different cell lines and demonstrates the necessity of training cell-line-specific models. Furthermore, we adopt Integrated Gradients to explain the proposed model in lncLocator 2.0, and find some potential patterns that determine the subcellular localizations of lncRNAs, suggesting that the subcellular localization of lncRNAs is linked to some specific nucleotides. Availabilityand implementation: The lncLocator 2.0 is available at ***/bioinf/lncLocator2 and the source code can be found at https://***/Yang-J-LIN/lncLocator2. © 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved.

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Monocular 3D tracking of deformable surfaces using linear programming

Monocular 3D tracking of deformable surfaces using linear pr...

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2010 20th International Conference on pattern recognition, ICPR 2010

作者： Wang, Chenhao Li, Xiong Liu, Yuncai Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9780769541099

We present a method for 3D shape reconstruction of inextensible deformable surfaces from monocular image sequences. The key of our approach is to represent the surface as 3D triangulated mesh and formulate the reconstruction problem as a sequence of Linear Programming (LP) problems which can be effectively solved. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which prevent large changes of the edge orientation between consecutive frames. Furthermore, we use a refined bisection algorithm to accelerate the computing speed. The robustness and efficiency of our approach are validated on both synthetic and real data. © 2010 IEEE.

关键词： Convex optimization

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Relative ordering learning based on weighted sparse representation for age estimation

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Journal of Information and Computational Science 2014年第14期11卷 4877-4888页

作者： Wang, Shengzheng Yang, Jie Merchant Marine College Shanghai Maritime University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

Age estimation has received extensively interest in computer vision field due to its wide applications, i.e. human behavior analysis, video content recognition, etc. Hence, many classification and regression approaches were widely used to estimate human age, and obtained the basically acceptable results, but the relative relationships of age groups have not been exploited in previous methods. Recently, much work proposed to use various ranking-based learning techniques to exploit the relative ordering information. This paper presents a novel relative ordering learning algorithm based on weighted sparse representation to advance the accuracy of age estimation. The age estimation problem is decomposed into a series of relative age ordering sub-problems, and the relative ordering learning of each sub-problem is performed by using weighted sparse representation. Thus, the human age is inferred by aggregating all relative comparison results. The greatest advantage is that the weighted value can be embedded into the age estimator, and also can be dynamically updated in term of the distributions of the training data. The proposed approach is validated in extensively used aging database FG-NET by comparing it with some existing state-of-the-art methods. The experimental results show that the proposed approach outperforms other methods in all cases, and can effectively solve the imbalance and inconsistency of the training data. 1548-7741/Copyright © 2014 Binary Information Press

关键词： Learning algorithms

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Hierarchical correlation stereo matching network 2nd

Hierarchical correlation stereo matching network

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2nd Chinese Conference on pattern recognition and Computer Vision, PRCV 2019

作者： Chen, Xuliang Zhou, Yue Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783030317256

Recently, stereo matching from a pair of rectified images has been cast as a supervised learning task using the powerful representation of convolutional neural networks. However, existing methods only utilize last feature maps output from Siamese Networks to compute similarity measurement, which are lack of multi-levels similarity information to construct an informative cost volume. To solve this problem, we propose a hierarchical correlation operation to compute similarity of stereo pairs at multiple levels. In addition, to yield accurate disparity in illposed region, we propose a stacked hourglass feature network with dense connections to effectively incorporate context information. Then, hybrid matching cost volume is built leveraging hierarchical correlation features and concatenation features of left and right. 3D CNN encoder-decoder architecture is utilized to regularize the cost volume and regress disparity. Experiments demonstrate that our network achieves competitive performance with state-of-the-art methods on Scene Flow, KITTI 2012, and KITTI 2015 datasets. © Springer Nature Switzerland AG 2019.

关键词： Neural networks

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Multi-sensor cost reference particle filtering algorithm based on consistency weight fusion

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Journal of Information and Computational Science 2012年第6期9卷 1675-1681页

作者： Hu, Zhentao Fu, Chunling Liu, Xianxing Li, Jie Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475004 China Basic Experiment Teaching Center Henan University Kaifeng 475004 China

Aiming at the state estimation of nonlinear system in multi-sensor observation uncertainty, a novel cost reference particle filter algorithm based on consistency weight fusion is proposed in this paper. Firstly, the cost function and the risk function are introduced to realize reasonable utilization of the latest observation. Secondly, the relative distance, the support degree function and matrix which are subject to the membership function characteristic of fuzzy set theory, are constructed to extract and use the redundancy and complementary information among particles weights measured by multi-sensor observation. Finally, particles weights are calculated by the information fusion method. The theoretical analysis and experimental results show the algorithm precision are effectively improved relative to standard particle filter and cost reference particle filter. © 2012 by Binary Information Press.

关键词： Cost functions

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