检索结果-内蒙古大学图书馆

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

来源：评论

学校读者我要写书评

暂无评论

Dual-Camera All-in-Focus Neural Radiance Fields

arXiv

引用

arXiv 2025年

作者： Luo, Xianrui Wu, Zijin Peng, Juewen Sun, Huiqiang Cao, Zhiguo Lin, Guosheng Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Singapore639798 Singapore

We present the first framework capable of synthesizing the all-in-focus neural radiance field (NeRF) from inputs without manual refocusing. Without refocusing, the camera will automatically focus on the fixed object for all views, and current NeRF methods typically using one camera fail due to the consistent defocus blur and a lack of sharp reference. To restore the all-in-focus NeRF, we introduce the dual-camera from smartphones, where the ultra-wide camera has a wider depth-of-field (DoF) and the main camera possesses a higher resolution. The dual camera pair saves the high-fidelity details from the main camera and uses the ultra-wide camera’s deep DoF as reference for all-in-focus restoration. To this end, we first implement spatial warping and color matching to align the dual camera, followed by a defocus-aware fusion module with learnable defocus parameters to predict a defocus map and fuse the aligned camera pair. We also build a multi-view dataset that includes image pairs of the main and ultra-wide cameras in a smartphone. Extensive experiments on this dataset verify that our solution, termed DC-NeRF, can produce high-quality all-in-focus novel views and compares favorably against strong baselines quantitatively and qualitatively. We further show DoF applications of DC-NeRF with adjustable blur intensity and focal plane, including refocusing and split diopter. Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Learning Dual-Domain Calibration and Distance-Driven Correlation Filter:A Probabilistic Perspective for UAV Tracking

引用

Computers, Materials & Continua 2023年第12期77卷 3741-3764页

作者： Taiyu Yan Yuxin Cao Guoxia Xu Xiaoran Zhao Hu Zhu Lizhen Deng Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and TelecommunicationsNanjingChina School of Computer Science Qufu Normal UniversityQufuChina National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjingChina

Unmanned Aerial Vehicle(UAV)tracking has been possible because of the growth of intelligent information technology in smart cities,making it simple to gather data at any time by dynamically monitoring events,people,the environment,and other aspects in the *** traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking *** these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization *** light of the aforementioned issues,this work suggests a dual-domain Jensen-Shannon divergence correlation filter(DJSCF)model address the probability-based distance measuring issue in the event of filter *** two-domain weighting matrix and JS divergence constraint are combined to lessen the impact of sample imbalance and *** new tracking models that are based on the perspectives of the actual probability filter distribution and observation probability filter distribution are proposed to translate the statistical distance in the online tracking model into response *** model is roughly transformed into a linear equality constraint issue in the iterative solution,which is then solved by the alternate direction multiplier method(ADMM).The usefulness and superiority of the suggested strategy have been shown by a vast number of experimental findings.

关键词： Dual-domain weighting distance measure correlation filter ADMM

来源：评论

学校读者我要写书评

暂无评论

Large Current Rectification Inside Symmetric Molecular Junctions Caused by Redox Coupled Conformational Changes

SSRN

引用

SSRN 2025年

作者： Lin, Jin-Liang Liu, Ran de Adoah, Francis Cao, Zhou Qiu, Shengzhe Chen, Ningyue Sun, Feng Wu, Zhikang Wang, Chuankui Xu, Bingqian de Barco, Enrique Li, Yuan Key Laboratory of Organic Optoelectronics Department of Chemistry Tsinghua University Beijing100084 China Department of Physics University of Central Florida OrlandoFL32816 United States Department of Physics and Astronomy & NanoSEC University of Georgia 220 Riverbend Road AthensGA30602 United States Biodesign Center for Bioelectronics and Biosensors Arizona State University TempeAZ85287 United States Key Laboratory of Medical Physics and Image Processing of Shandong Province School of Physics and Electronics Shandong Normal University Jinan250358 China School of Physics Ningxia University Yinchuan750021 China

The ability to test the limit of a diode downsize to molecular (quantum) scale that can help the development of nanoelectronic devices. So far, Strategies for molecular rectification have mostly relied on the intrinsic asymmetry of molecule or on changes in the external environment. These approaches require complex synthetic designs or specific device structures, and performances are far beyond the theoretical prediction. Here we report an alternative strategy that leads to giant rectification in molecular tunnel junctions by inducing a topological change of the molecular conformation through unidirectional electric-field-driven electron delocalization, an approach also applicable to molecules without asymmetric structures. This is achieved by reversing the polarity of the applied bias potential, which induces the rectifying group to oxidize, transitioning from a buckled and cross-conjugated group into a planar aromatic group. As a result, the transformed molecule forms a fully conjugated molecular structure resulting in a substantial increase in the current density. © 2025, The Authors. All rights reserved.

关键词： Molecules

来源：评论

学校读者我要写书评

暂无评论

UniAnimate-DiT: Human image Animation with Large-Scale Video Diffusion Transformer

arXiv

引用

arXiv 2025年

作者： Wang, Xiang Zhang, Shiwei Tang, Longxiang Zhang, Yingya Gao, Changxin Wang, Yuehuan Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology United States Alibaba Group China Tsinghua University China

This report presents UniAnimate-DiT, an advanced project that leverages the cutting-edge and powerful capabilities of the open-source Wan2.1 model for consistent human image animation. Specifically, to preserve the robust generative capabilities of the original Wan2.1 model, we implement Low-Rank Adaptation (LoRA) technique to fine-tune a minimal set of parameters, significantly reducing training memory overhead. A lightweight pose encoder consisting of multiple stacked 3D convolutional layers is designed to encode motion information of driving poses. Furthermore, we adopt a simple concatenation operation to integrate the reference appearance into the model and incorporate the pose information of the reference image for enhanced pose alignment. Experimental results show that our approach achieves visually appearing and temporally consistent high-fidelity animations. Trained on 480p (832x480) videos, UniAnimate-DiT demonstrates strong generalization capabilities to seamlessly upscale to 720P (1280x720) during inference. The training and inference code is publicly available at https://github. com/ali-vilab/UniAnimate-DiT. Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

引用

Journal of Electronics(China) 2012年第3期29卷 197-203页

作者： Hu Xiaofei Zhu Xiuchang Image Processing and Image Communication Key Laboratory Nanjing University of Posts and Telecommunications Nanjing 210003 China College of Geography and Biological Information Nanjing University of Posts and Telecommunications Nanjing 210003 China

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

关键词： Transform domain Wyner-Ziv (WZ) DIStributed COding for Video sERvices (DISCOVER) Video coding Correlation noise model Mixture Laplace-Uniform Distribution Model (MLUDM)

来源：评论

学校读者我要写书评

暂无评论

Dynamic Color Transform Networks for Wheat Head Detection

引用

Plant Phenomics 2022年第1期4卷 395-408页

作者： Chengxin Liu Kewei Wang Hao Lu Zhiguo Cao Key Laboratory of Image Processing and Intelligent Control Ministry of EducationSchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina

Wheat head detection can measure wheat traits such as head density and head *** wheat breeding largely relies on manual observation to detect wheat heads,yielding a tedious and inefficient *** emergence of affordable camera platforms provides opportunities for deploying computer vision(CV)algorithms in wheat head detection,enabling automated measurements of wheat *** wheat head detection,however,is challenging due to the variability of observation circumstances and the uncertainty of wheat head *** this work,we propose a simple but effective idea—dynamic color transform(DCT)—for accurate wheat head detection.

关键词： Wheat breeding wheat

来源：评论

学校读者我要写书评

暂无评论

A Survey on Negative Transfer

引用

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 305-329页

作者： Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China IEEE the School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

Transfer learning(TL)utilizes data or knowledge from one or more source domains to facilitate learning in a target *** is particularly useful when the target domain has very few or no labeled data,due to annotation expense,privacy concerns,***,the effectiveness of TL is not always *** transfer(NT),i.e.,leveraging source domain data/knowledge undesirably reduces learning performance in the target domain,and has been a long-standing and challenging problem in *** approaches have been proposed in the literature to address this ***,there does not exist a systematic *** paper fills this gap,by first introducing the definition of NT and its causes,and reviewing over fifty representative approaches for overcoming NT,which fall into three categories:domain similarity estimation,safe transfer,and NT *** areas,including computer vision,bioinformatics,natural language processing,recommender systems,and robotics,that use NT mitigation strategies to facilitate positive transfers,are also ***,we give guidelines on NT task construction and baseline algorithms,benchmark existing TL and NT mitigation approaches on three NT-specific datasets,and point out challenges and future research *** ensure reproducibility,our code is publicized at https://***/chamwen/NT-Benchmark.

关键词： Domain adaptation domain similarity negative transfer positive transfer transfer learning

来源：评论

学校读者我要写书评

暂无评论

Multi-view synthesis using the relative affine structure from video sequences

Multi-view synthesis using the relative affine structure fro...

引用

International Conference on Multimedia and Signal processing (CMSP)

作者： Huo, Zhiyong Liu, Tianliang Zhu, Xiuchang Jiangsu Key Laboratory of Image Processing and Communication Nanjing Univ. of Posts and Telecommun. Nanjing China

ISBN: (纸本)9780769543567

This paper proposes an approach for Multi-view synthesis, the process of view synthesis based on the relative affine structure. We specifying the virtual camera position in an uncalibrated setting, based on the interpolation of the motion among the reference views. Novel images can be rendered from virtual cameras moving on parametric trajectories. Synthetic and real experiments illustrate the approach. © 2011 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Stereo matching using aggregated likelihood and multi-scale prior

Stereo matching using aggregated likelihood and multi-scale ...

引用

2012 3rd IEEE/IET International Conference on Audio, Language and image processing, ICALIP 2012

作者： Wang, Liang Liu, Tianliang Zhu, Xiuchang Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781467301718

This paper proposes a novel global stereo matching method using aggregated likelihoods and multi-scale priors. The likelihoods of dense stereo correspondences as data term can be robustly expressed by aggregated matching costs based on Weber feature descriptors in an asymmetrical linear filtering model. The multi-scale priors on disparity surface are designed to capture scene smooth term from larger neighborhood besides 4-connected neighborhood. The presented stereo approach being relatively simple does not rely on image segmentation and any scene semantic analysis. Experiments demonstrate that the proposed stereo matching algorithm can produce the dense smooth disparity results comparable to those of excellent stereo matching techniques. © 2012 IEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：