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IEEE Transactions on Computational Biology and Bioinformatics 2025年第1期22卷 355-367页

作者： Cheng Cai Zhaohong Deng Andong Li Yun Zuo Haoran Chen Zhisheng Wei Lei Wang Xiaoyong Pan Hong-Bin Shen Dong-Jun Yu School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University Shanghai China School of Biotechnology Jiangnan University Wuxi China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

The development of intelligent methods capable of predicting protein-ligand binding sites has become a popular research field. Recently, deep learning based methods have been proposed as a promising solution for this task. However, some limitations still exist. For example, the network structure is not optimized for predicting protein binding pockets, which limits the model's capabilities. To address the aforementioned challenges, a novel method called CATransUnetLPB is proposed, in which a new network structure named CATransUnet is designed. The proposed CATransUnet combines CNN and Transformer models to accurately segment binding pocket regions from protein 3D structures. It outperforms existing representative methods on three test sets, demonstrating the effectiveness of optimizing the deep network model for detecting protein ligand binding pockets. Furthermore, we conduct thorough analysis on applying data augmentation to protein data structure and confirm that such technique can enhance the model's generalization ability, thereby ensuring good performance on new protein structures. Moreover, experiments show that the predicted binding pockets from our model can complement the results obtained from other methods. This suggests that integrating our method with existing approaches could further improve the prediction of protein-ligand binding pockets.

关键词： Proteins Three-dimensional displays Probes Vectors image segmentation Deep learning Atoms Surface treatment Prediction algorithms Training

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Overexposure correction by mixed one-bit compressive sensing for C-Arm CT 1

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Workshops on image processing for the medicine, 2017

作者： Huang, Xiaolin Xia, Yan Huang, Yixing Hornegger, Joachim Maier, Andreas Pattern Recognition Lab Friedrich-Alexander-University Erlangen-Nürnberg Germany Department of Radiology Stanford University United States Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (数字)9783662543450

ISBN: (纸本)9783662543443

This paper proposes a novel method to deal with overexposure for C-arm CT reconstruction. The proposed method is based on recent progress of one bit compressive sensing (1bit-CS), which is to recover sparse signals from sign measurements. Overexposure could be regarded as a kind of sign information, thus the application of 1bit-CS to overexposure correction in CT reconstruction is expected. This method is evaluated on a phantom and its promising performance implies potential application on clinical data. © Springer-Verlag GmbH Deutschland 2017.

关键词： Compressed sensing

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Comparing and integrating alignment template and standard phrase-based statistical machine translation

Comparing and integrating alignment template and standard ph...

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8th International Conference on Intelligent Text processing and Computational Linguistics

作者： Xu, Lin Cao, Xiaoguang Zhang, Bufeng Li, Mu Lab. of Pattern Recognition and Intelligent System Image Processing Center BeiHang University China Al Lab. Computer Science and Technology Tianjing University China Microsoft Research Asia China

ISBN: (纸本)9783540709381

In statistical machine translation (SMT) research, phrase-based methods have been receiving more interest in recent years. In this paper, we first give a brief survey of phrase-based SMT framework, and then make detailed comparisons of two typical implementations: alignment template approach and standard phrase-based approach. At last, we propose an improved model to integrate alignment template into standard phrase-based SMT as a new feature in a log-linear model. Experimental results show that our method outperforms the baseline method.

关键词： Natural language processing systems

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A new fuzzy ART neural network based on dual competition and resonance technique

A new fuzzy ART neural network based on dual competition and...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Zhang, Lei Wang, Guoyou Wang, Wentao Lab. for Biometric and Medical Image Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)354034439X

A new Fuzzy ART neural network model based on dual competition and resonance technique is proposed. This new model takes the competition and resonance method of the input nodes into the output nodes, putting the input nodes and output nodes competition and resonance together, solves the over-segmentation of the FART algorithm due to the vigilance's increase in the application of the image segmentation. Experimental results have shown that compared with the original FART, this algorithm has a better segmentation and antinoise performance. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Neural networks

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A comparative study of radial basis function neural networks in dynamic clustering algorithm

A comparative study of radial basis function neural networks...

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MIPPR 2009 - pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Zhou, Peng Li, Dehua Wu, Hong Zeng, Jun Chen, Feng State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the stepwise-regression algorithm of the ICc mages the model structure independent of the selected term sequence and reduces the cluster region further as compared with orthogonal least squares (OLS). as the Bayesian information criteria (BIC) method is incorporate into the clustering process of the ICc, except for the widths of Gaussian functions, it has no other parameter that need tuning ,but the user is required to specify the tolerance ρ, which is relevant to noises and will be difficult to implement in the real system, for the OLS algorithm. The two algorithms are employed to the Radial Basis Function Neural Networks (RBFNN) to compare its performance for different noise nonlinear dynamic systems. Experimental results show that they provide an efficient approximation to the required results for fitting models, but the clustering procedures of the ICc is substantially better solutions than does the OLS. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Radial basis function networks

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Integer Haar wavelet for romote sensing image compression 6

Integer Haar wavelet for romote sensing image compression

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6th International Conference on Signal processing, ICSP 2002

作者： Zhenhua, Wang Hongbo, Xu Yan, Tian Jinwen, Tian Jian, Liu State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)0780374886

With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction approach of integer Haar is discussed briefly, and a'simple image compression scheme based on integer Haar Wavelet Transform and block DPCM is proposed. The scheme can be easily designed for data processing in real-time system of remote sensing with parellel algorithm. Simulation experimental results demonstrate that the proposed approach is a efficient image compression method. © 2002 IEEE.

关键词： image compression

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Motion Planning and Tracking Control Method Based on CoppeliaSim for UGV in Irregular Terrain 5

Motion Planning and Tracking Control Method Based on Coppeli...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Huang, Jiale Chen, Zhihua Zhong, Yongbo Zeng, Wenrui Ji, Chuanmin Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China

ISBN: (纸本)9798350307320

Path planning and tracking algorithms are one of the cores of autonomous navigation technology for unmanned ground vehicle (UGV). In this paper, a local obstacle avoidance method based on event-triggered control is proposed to ensure that the UGV avoids obstacles in the tracking process. First, the path planning and tracking control problem of the UGV is modeled and formulated. Second, the improvement and logical correlation of the relevant algorithms are described in detail. Finally, ajoint simulation of MATlab and V-rep is performed. The simulation results show that event-triggered control can largely improve the reliability of the UGV path planning and tracking process, and verify the effectiveness of the algorithm. © 2023 IEEE.

关键词： Motion planning

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Feedback-free and hybrid distributed video coding using neural networks

Feedback-free and hybrid distributed video coding using neur...

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2012 11th International Conference on Information Science, Signal processing and their Applications, ISSPA 2012

作者： Nickaein, Isaac Rahmati, Mohammad Ghidary, Saeed Shiry Zohrabi, Abtin Image Processing and Pattern Recognition Lab Department of Computer Engineering and IT Amirkabir University of Technology Tehran Iran Abtin Zohrabi Faculty of Computer Science University of New Brunswick Canada

ISBN: (纸本)9781467303828

Distributed Video Coding (DVC) is a new class of video coding techniques with the aim of coding the decentralized video sources. While the Stanford Wyner-Ziv codec is a well-known architecture in DVC literature, one of its main drawbacks is the presence of a feedback channel from the decoder to the encoder. This feedback channel makes the use of the codec impractical in some applications. Since the only application of the feedback channel is in requesting more parity bits from the encoder, it could be omitted if the encoder estimates the required parity bits and sends them at once. In this paper, a new method of bitrate estimation using a neural network trained by a new set of features is proposed. In addition, a Hybrid mode is proposed that reduces computational complexity at the decoder in a conventional Wyner-Ziv codec. © 2012 IEEE.

关键词： image coding

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A new noise erosion operator for anisotropic diffusion

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Chinese Optics Letters 2004年第5期2卷 268-270页

作者：蔡超丁名跃周成平张天序 Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Lab for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

A noise erosion operator based on partial differential equation (PDE) is introduced, which has an excellent ability of noise removal and edge preservation for two-dimensional (2D) gradient data. The operator is applied to estimate a new diffusion coefficient. Experimental results demonstrate that anisotropic diffusion based on this new erosion operator can efficiently reduce noise and sharpen object boundaries.

关键词： Anisotropic diffusion Diffusion

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An adaptive nonparametric discriminant analysis method and its application to face recognition

An adaptive nonparametric discriminant analysis method and i...

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8th Asian Conference on Computer Vision, ACCV 2007

作者： Huang, Liang Yong, Ma. Ijiri, Yoshihisa Lao, Shihong Kawade, Masato Zhao, Yuming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Sensing and Control Technology Lab. Omron Corporation Kyoto 619-0283 Japan

ISBN: (纸本)9783540763895

Linear Discriminant Analysis (LDA) is frequently used for dimension reduction and has been successfully utilized in many applications, especially face recognition. In classical LDA, however, the definition of the between-class scatter matrix can cause large overlaps between neighboring classes, because LDA assumes that all classes obey a Gaussian distribution with the same covariance. We therefore, propose an adaptive nonparametric discriminant analysis (ANDA) algorithm that maximizes the distance between neighboring samples belonging to different classes, thus improving the discriminating power of the samples near the classification borders. To evaluate its performance thoroughly, we have compared our ANDA algorithm with traditional PCA+LDA, Orthogonal LDA (OLDA) and nonparametric discriminant analysis (NDA) on the FERET and ORL face databases. Experimental results show that the proposed algorithm outperforms the others. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Face recognition

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