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arXiv 2025年

作者： Gao, Chengrui Yang, Ziyuan Jia, Wei Leng, Lu Zhang, Bob Teoh, Andrew Beng Jin College of Computer Science Sichuan University Chengdu610065 China Singapore School of Computer and Information Hefei University of Technology Hefei China Jiangxi Provincial Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China Pattern Analysis and Machine Intelligence Group Department of Computer and Information Science University of Macau Taipa China School of Electrical and Electronic Engineering College of Engineering Yonsei University Seoul Korea Republic of

Palmprint recognition has emerged as a prominent biometric technology, widely applied in diverse scenarios. Traditional handcrafted methods for palmprint recognition often fall short in representation capability, as they heavily depend on researchers' prior knowledge. Deep learning (DL) has been introduced to address this limitation, leveraging its remarkable successes across various domains. While existing surveys focus narrowly on specific tasks within palmprint recognition-often grounded in traditional methodologies-there remains a significant gap in comprehensive research exploring DL-based approaches across all facets of palmprint recognition. This paper bridges that gap by thoroughly reviewing recent advancements in DL-powered palmprint recognition. The paper systematically examines progress across key tasks, including region-of-interest segmentation, feature extraction, and security/privacy-oriented challenges. Beyond highlighting these advancements, the paper identifies current challenges and uncovers promising opportunities for future research. By consolidating state-of-the-art progress, this review serves as a valuable resource for researchers, enabling them to stay abreast of cutting-edge technologies and drive innovation in palmprint recognition. Copyright © 2025, The Authors. All rights reserved.

关键词： Biometrics

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Discovering the nuclear localization signal universe through a deep learning model with interpretable attention units

Patterns

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patterns 2025年

作者： Yi-Fan Li Xiaoyong Pan Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

We describe NLSExplorer, an interpretable approach for nuclear localization signal (NLS) prediction. By utilizing the extracted information on nuclear-specific sites from the protein language model to assist in NLS detection, NLSExplorer achieves superior performance with greater than 10% improvement in the F1 score compared with existing methods on benchmark datasets and highlights other nuclear transport segments. We applied NLSExplorer to the nucleus-localized proteins in the Swiss-Prot database to extract valuable segments. A comprehensive analysis of these segments revealed a potential NLS landscape and uncovered features of nuclear transport segments across 416 species. This study introduces a powerful tool for exploring the NLS universe and provides a versatile network that can efficiently detect characteristic domains and motifs.

关键词： nuclear localization signals prediction protein language model database mining deep learning interpretation

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Segmentation of the Ventricle Membranes in Short-Axis Sequences by Optical Flow Base on DLSRE Model

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Chinese Journal of Electronics 2021年第3期30卷 460-470页

作者： LI Lin WU Hengfei LI Junhua Department of Electronics and Information Engineering Bozhou University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University

Recent studies have pointed out that the boundary of the extracted ventricle membranes is unsmooth, and the segmentation of the cardiac papillary muscle and trabecular muscle do inconformity the clinical requirements. To address these issues, this paper proposes an automatic segment algorithm for continuously extracting ventricle membranes boundary, which adopts optical flow field information and sequential images information. The images are cropped by frame difference method, which according to the continuity of adjacent slices of cardiac MRI images. The roughly boundary of epicardium is extracted by the Double level set region evolution(DLSRE) model, which combines image global information, local information and edge information. The ventricle endocardium and epicardial contours are tracked according to the optical flow field information between image sequences. The segmentation results are optimized by Delaunay triangulation algorithm. The experimental results demonstrate that the proposed method can improve the accuracy of segmenting the ventricle endocardium and epicardium contours, and segment the contour of the smooth ventricle membrane edge that meets the clinical definition.

关键词： edge information image sequences automatic segment algorithm sequential images information clinical requirements medical image processing cardiology optical flow base extracted ventricle membranes roughly boundary local information ventricle endocardium trabecular muscle optical flow field information continuously extracting ventricle membranes boundary DLSRE model biomedical MRI smooth ventricle membrane edge image global information mesh generation muscle short-axis sequences cardiac MRI images image segmentation cardiac papillary muscle frame difference method region evolution model

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Fast hybrid fitting energy-based active contour model for target detection

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Chinese Optics Letters 2011年第7期9卷 29-32页

作者：王登位张天序颜露新 State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

A novel hybrid fitting energy-based active contour model in the level set framework is proposed. The method fuses the region and boundary information of the target to achieve accurate and robust detection performance. A special extra term that penalizes the deviation of the level set function from a signed distance function is also included in our method. This term allows the time-consuming redistancing operation to be removed completely. Moreover, a fast unconditionally stable numerical scheme is introduced to solve the problem. Experimental results on real infrared images show that our method can improve target detection performance efficiently in terms of the number of iterations and the wasted central processing unit （CPU） time.

关键词： Infrared imaging Program processors

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High performance reconfigurable hardware system for real-time image processing

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Journal of Systems Engineering and Electronics 2005年第3期16卷 502-509页

作者：赵广州张天序王岳环曹治国左峥嵘 State Key Laboratory for I mage Processing and Intelligent Control Inst .for Pattern Recognition and Artificial Intelligence Huazhong Univ .of Science and Technology

A novel reconfigurable hardware system which uses both muhi-DSP and FPGA to attain high performance and real-time image processing are presented. The system structure and working principle of mainly processing multi-BSP board, extended multi-DSP board are analysed. The outstanding advantage is that the communication among different board components of this system is supported by high speed link ports ＆ serial ports for increasing the system performance and computational power. Then the implementation of embedded real-time operating systems （RTOS） by us is discussed in detail. In this system, we adopt two kinds of parallel structures controlled by RTOS for parallel processing of algorithms. The experimental results show that exploitive period of the system is short, and maintenance convenient. Thus it is suitable for real-time image processing and can get satisfactory effect of image recognition.

关键词： multi-DSP fidd programmable gate arrays real-time image processing real time operating systems parallel structure.

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Bioimage-based protein subcellular location prediction： a comprehensive review

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Frontiers of Computer Science 2018年第1期12卷 26-39页

作者： Ying-Ying XU Li-Xiu YAO Hong-Bin SHEN Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging techniques, the usage of 2D bioimages has become increasingly popular in automatically analyzing the protein subcellular location pat- terns. Compared with the widely used protein 1D amino acid sequence data, the images of protein distribution are more intuitive and interpretable, making the images a better choice at many applications for revealing the dynamic char- acteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systemati- cally reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and clas- sified them into four categories including growing of bioim- age databases, description of subcellular location distribution patterns, classification methods, and applications of the pre- diction systems. Besides, we also discussed some potential directions in this field.

关键词： bioimage informatics protein subcellular loca-tion prediction global and local features multi-location pro-tein recognition

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Shadow detection using regression tree fields with paired regions

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Journal of Computational Information Systems 2013年第11期9卷 4309-4317页

作者： Tao, Wei Zhou, Yue Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

In this paper, we try to deal with the problem of shadow detection from static images and video sequences. In instead to considering individual regions separately, we use relative illumination conditions between segmented regions and perform pair-wise classification based on such information. We use Regression Tree Fields to solve the labeling of shadow and non-shadow regions. And we use continuous value to describe the possibility of the shadow of the region. We evaluate our method on static images and a series of video sequences. © 2013 by Binary Information Press.

关键词： Classification (of information)

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Motion cue based pedestrian detection with two-frame-filtering

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High Technology Letters 2015年第3期21卷 328-332页

作者：吕敬钦 Zhang Miaohui Yang Jie Institute of Image Processing and Pattern Recognition Shanghai Jiaotong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.

关键词： pedestrian detection two-frame-filtering (TFF) Tff magnitude vector (TffMV) Histogram of Tff oriented gradient ( HTffOG) SVM video surveillance

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Image matching navigation based on fuzzy information

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Journal of Harbin Institute of Technology(New Series) 2003年第4期10卷 447-449页

作者：田玉龙吴伟仁田金文柳健 State Key Laboratory for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

关键词： image matching fuzzy information similarity

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An Adaptive Regulation Problem and Its Application

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International Journal of Automation and computing 2017年第2期14卷 221-228页

作者： Yuan Jiang Ji-Yang Dai Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang 330063 China School of Information Engineering Nanchang Hangkong University Nanchang 330063 China

This paper studies an adaptive regulation problem for the modified FitzHugh-Nagumo neuron model under external electrical stimulation. We first present the solution of the global robust output regulation problem for output feedback system with an uncertain exosystem which models the external electrical stimulation with unknown frequency and amplitude. Then, we show that the robust control problem for the modified FitzHugh-Nagumo neuron model can be formulated as the global robust output regulation problem and the solvability conditions for the output regulation problem for the modified FitzHugh-Nagumo neuron model are all satisfied. Then, we apply the obtained output regulation result to constructing an output feedback control law for the modified FitzHugh-Nagumo neuron model to achieve global stability of the closed-loop system in the presence of uncertain parameters and external stimulus. An example is given to show that the proposed algorithm can completely reject the external electrical stimulation.

关键词： Control theory Lyapunov methods internal model principle modified FitzHugh-Nagumo model.

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