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Deep learning for iris recognition: a review

Neural Computing and Applications 2025年 1-49页

作者： Yin, Yimin He, Siliang Zhang, Renye Chang, Hongli Zhang, Jinghua School of Mathematics and Statistics Hunan First Normal University Hunan Changsha410205 China School of Computer Science Hunan First Normal University Changsha410205 China School of Information Science and Engineering Southeast University Nanjing210096 China College of Intelligence Science and Technology National University of Defense Technology Hunan Changsha410073 China

Iris recognition is a secure biometric technology known for its stability and privacy. With no two irises being identical and little change throughout a person’s lifetime, iris recognition is considered more reliable and less susceptible to external factors than other biometric recognition methods. Unlike traditional machine learning-based iris recognition methods, deep learning technology does not rely on feature engineering and boasts excellent performance. This paper collects 131 relevant papers to summarize the development of iris recognition based on deep learning. We introduce the background of iris recognition and the motivation and contribution of this survey. Then, we present the common datasets widely used in iris recognition. After that, we summarize the key tasks involved in the process of iris recognition based on deep learning technology, including identification, segmentation, presentation attack detection, and localization. Finally, we discuss the challenges and potential development of iris recognition. This review provides a comprehensive sight of the research of iris recognition based on deep learning. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Contrastive Learning

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Elaboration of a Conceptual Map of E-WOM Through Co-Word Analysis

Elaboration of a Conceptual Map of E-WOM Through Co-Word Ana...

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International Conference on Marketing and Technologies, ICMarkTech 2023

作者： Carrasco, Ramón A. Bueno, Itzcóatl Cobo, Manuel Ruiz, Gricela Elizabeth Andrade Statistics Faculty Complutense University of Madrid Madrid Spain Department of Computer Science and AI University of Granada Granada Spain Complutense University of Madrid Madrid Spain

ISBN: (纸本)9789819736973

In present-day marketing, electronic customer reviews contained in e-commerce platforms (Amazon, AliExpress…), social networks (Twitter, TripAdvisor, Facebook…), etc., are a key factor to measure and manage as customers often base their purchase decision on these reviews. As a result, this area, which has come to be known as electronic-word-of-mouth (E-WOM), has generated great interest in the scientific literature. This paper proposes a conceptual map of this area to guide both E-WOM research scientists and marketers. This map is composed of layers: data, techniques and methods, and applications. To build it, we have used the scientific literature published in this area and bibliometric techniques to analyze it. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sales

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Multi-Level Feature Distillation of Joint Teachers Trained on Distinct Image Datasets

Multi-Level Feature Distillation of Joint Teachers Trained o...

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2025 IEEE/CVF Winter Conference on Applications of computer Vision, WACV 2025

作者： Iordache, Adrian Alexe, Bogdan Ionescu, Radu Tudor University of Bucharest Department of Computer Science Bucharest Romania 'Gheorghe Mihoc - Caius Iacob' Institute of Mathematical Statistics and Applied Mathematics The Romanian Academy Bucharest Romania

ISBN: (纸本)9798331510831

We propose a novel teacher-student framework to distill knowledge from multiple teachers trained on distinct datasets. Each teacher is first trained from scratch on its own dataset. Then, the teachers are combined into a joint architecture, which fuses the features of all teachers at multiple representation levels. The joint teacher architecture is fine-tuned on samples from all datasets, thus gathering useful generic information from all data samples. Finally, we employ a multi-level feature distillation procedure to transfer the knowledge to a student model for each of the considered datasets. We conduct image classification experiments on seven benchmarks, and action recognition experiments on three benchmarks. To illustrate the power of our feature distillation procedure, the student architectures are chosen to be identical to those of the individual teachers. To demonstrate the flexibility of our approach, we combine teachers with distinct architectures. We show that our novel Multi-Level Feature Distillation (MLFD) can significantly surpass equivalent architectures that are either trained on individual datasets, or jointly trained on all datasets at once. Furthermore, we confirm that each step of the proposed training procedure is well motivated by a comprehensive ablation study. We publicly release our code at https://***/AdrianIordache/MLFD. © 2025 IEEE.

关键词： Teaching

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Turán Numbers for Vertex-disjoint Triangles and Pentagons

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Acta Mathematica Sinica,English Series 2025年第4期41卷 1181-1195页

作者： Fangfang Wu Hajo Broersma Shenggui Zhang Binlong Li School of Mathematics and Statistics Hunan Normal University Faculty of Electrical Engineering Mathematics and Computer Science University of Twente School of Mathematics and Statistics Northwestern Polytechnical University Xi'an-Budapest Joint Research Center for Combinatorics Northwestern Polytechnical University

The Turán number,denoted by ex（n,H）,is the maximum number of edges of a graph on n vertices containing no graph H as a *** by kClthe union of k vertex-disjoint copies of *** this paper,we present new results for the Turán numbers of vertex-disjoint *** first results deal with the Turán number of vertex-disjoint triangles ex（n,kC3）.We determine the Turán number ex（n,kC3） for n≥k2+5k/2 when k≤4,and n≥k2+2 when k≥***,we give lower and upper bounds for ex（n,kC3） with 3k≥n≤k2+5k/2 when k≤4,and 3k≤n≤k2+2 when k≥***,we give a lower bound for the Turán number of vertex-disjoint pentagons ex（n,kC5）.Finally,we determine the Turán number ex（n,kC5） for n=5k,and propose two conjectures for ex（n,kC5） for the other values of n.

关键词： 05B05 05B25 20B25 extremal graphs Turán number vertex-disjoint pentagons vertex-disjoint triangles

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A quantitative investigation of immigrants integration and detention in Europe

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Quality and Quantity 2025年第1期59卷 253-274页

作者： Ballerini, Veronica Seri, Emiliano Department of Statistics Computer Science Applications “G. Parenti” University of Florence Florence Italy Department of Enterprise Engineering “Mario Lucertini” University of Rome Tor Vergata Rome Italy

In this paper, we question whether different attitudes of European countries’ policies toward migrant integration correspond to different propensities to hold foreigners in prison. As a first attempt to test the existence of such an association, we cluster 34 European countries for the year 2019, modelling the dimensions of the Migrant Integration Policy Index (MIPEX). Leveraging finite mixtures of multivariate Gaussian, we identify three groups of countries with a similar level of integration. Then, we estimate the relative proportion of foreigners held in prison among clusters, relying on UNODC and UNDESA data and exploiting Fisher’s noncentral hypergeometric (FNCH) model. We aim to introduce the FNCH model on clusters as a new quantitative tool to investigate demographic and social research issues. Results show that, in the less virtuous cluster in terms of migrants’ integration, foreigners are almost twice more exposed to detention than in the other clusters. Moreover, looking at the differences within clusters, we find that foreigners have a different propensity to be held in prison with respect to citizens. The proposed approach adds new valuable insights to the MIPEX and provides a novel perspective on an important and highly debated phenomenon, such as foreigners in prison, through the lenses of migrants’ integration. From a policymaking perspective, there emerges a need for more attention and further investigation on the paths underlying such an association between migrants’ integration and detention. To this aim, it is essential that countries enhance data collection and access, especially on migrant incarceration. © The Author(s) 2024.

关键词： Foreigners in prison MIPEX Model-based clustering Noncentral hypergeometric distribution Odds ratios

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VARIABLE SCREENING AND SPATIAL SMOOTHING IN FRÉCHET REGRESSION WITH APPLICATION TO DIFFUSION TENSOR IMAGING

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Annals of Applied statistics 2025年第1期19卷 655-679页

作者： Yan, Lei Zhang, Xin Lan, Zhou Bandyopadhyay, Dipankar Wu, Yichao Department of Statistics Florida State University United States Department of Radiology Brigham and Women’s Hospital Harvard Medical School United States Department of Biostatistics Virginia Commonwealth University United States Department of Mathematics Statistics and Computer Science University of Illinois United States

Modern applications in medical imaging often include high-dimensional predictors and spatially dependent responses in the non-Euclidean space. For example, in imaging-genetics studies, our objective is to study the relationship between single-nucleotide polymorphisms (SNPs), a high-dimensional predictor vector, and diffusion tensor imaging (DTI) responses, which are thousands to millions of voxelwise 3 × 3 symmetric positive definite (SPD) matrices. In this paper we develop a fast and pragmatic method of regressing spatially associated random responses on a high-dimensional predictor set. Specifically, we focus on two related problems: fast variable screening of high-dimensional predictors and smoothing techniques for nonEuclidean spatially associated responses. Under a Fréchet regression framework (which handles regression of SPD matrix-variate responses on covariates in Euclidean space), we propose a two-stage approach, where a screening method (using distance covariances in metric spaces) is employed to mitigate high-dimensionality (Stage 1), followed by deriving a closed-form solution that powers elegant smoothing of the spatially associated SPD responses (Stage 2). We investigate the finite-sample properties of our method using synthetic data generated under various settings and present illustration via analysis of an imaging-genetics (DTI responses with genetic and demographic predictors) dataset, derived from the Alzheimer’s Disease Neuroimaging Initiative 2. Code for implementing our proposed method is available in the GitHub link:. © Institute of Mathematical statistics, 2025.

关键词： Diffusion tensor imaging distance covariance Fréchet regression smoothing sure screening property

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Sampling List Packings 16

Sampling List Packings

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16th Innovations in Theoretical computer science Conference, ITCS 2025

作者： Camrud, Evan Davies, Ewan Karduna, Alex Lee, Holden Department of Mathematics and Statistics Middlebury College VT United States Department of Computer Science Colorado State University Fort CollinsCO United States Department of Applied Mathematics and Statistics Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9783959773614

We initiate the study of approximately counting the number of list packings of a graph. The analogous problem for usual vertex coloring and list coloring has attracted substantial attention. For list packing the setup is similar, but we seek a full decomposition of the lists of colors into pairwise-disjoint proper list colorings. The existence of a list packing implies the existence of a list coloring, but the converse is false. Recent works on list packing have focused on existence or extremal results of on the number of list packings, but here we turn to the algorithmic aspects of counting and sampling. In graphs of maximum degree ∆ and when the number of colors is at least Ω(∆2), we give a fully polynomial-time randomized approximation scheme (FPRAS) based on rapid mixing of a natural Markov chain (the Glauber dynamics) which we analyze with the path coupling technique. Some motivation for our work is the investigation of an atypical spin system, one where the number of spins for each vertex is much larger than the graph degree. © Evan Camrud, Ewan Davies, Alex Karduna, and Holden Lee.

关键词： Markov chains

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Conformal Composition for Borderline Fractional Sobolev Spaces

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Acta Mathematica Sinica,English Series 2025年第1期41卷 457-471页

作者： Nijjwal Karak Pekka Koskela Debanjan Nandi Swadesh Kumar Sahoo Department of Mathematics Birla Institute of Technoogy and Science Pilani-Hyderabad CampusHyderabad 500078India Department of Mathematics and Statistics University of JyvèaskylèaP.O.Box 35FI-40014 JyvèaskylèaFinland Faculty of Mathematics and Computer Science Weizmann Institute of Science234 Herzl StreetRehovot 76100Israel Department of Mathematics Indian Institute of Technology IndoreIndore 453552India

We establish a pointwise property for homogeneous fractional Sobolev spaces in domains with non-empty boundary,extending a similar result of Koskela–Yang–*** use this to show that a conformal map from the unit disk onto a simply connected planar domain induces a bounded composition operator from the borderline homogeneous fractional Sobolev space of the domain into the corresponding space of the unit disk.

关键词： Besov Hajlasz–Triebel–Lizorkin hyperbolic conformal

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TEDME-KG Metrics Framework: A Metrics Framework for TEmporal Data Modelling Evaluation in Knowledge Graphs 6th

TEDME-KG Metrics Framework: A Metrics Framework for TEmporal...

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6th International Conference on Knowledge Graphs and Semantic Web, KGSWC 2024

作者： Hooshafza, Sepideh Yaman, Beyza Randles, Alex Little, Mark Stephens, Gaye ADAPT Research Centre School of Computer Science and Statistics Trinity College Dublin Dublin Ireland Trinity Health Kidney Centre Trinity College Dublin Dublin Ireland

ISBN: (纸本)9783031812200

Temporal data modelling in Knowledge Graphs (KGs) refers to the practice of modelling time-varying information in a structured manner. Representing temporal data, enhances KGs’ capabilities by providing comprehensive time-dependent information, making it important for knowledge representation and analysis in various real-world applications. Organisations can enhance data management, user experience, and decision-making processes in their KG applications by selecting the most suitable temporal data modelling approach. Many approaches have been proposed to model temporal data in KGs but they have not been fully evaluated with different metrics. Evaluating different temporal data modelling approaches in KGs using a metrics framework assists objective comparison, informed decision-making, and the advancement of the field. This paper proposes TEDME-KG Metrics Framework, a Metrics Framework for TEmporal Data Modelling Evaluation in Knowledge Graphs. The framework was developed through a comprehensive literature review and the application of the Goal Question Metrics (GQM) method during the design and evaluation of KGs for selected temporal data modelling approaches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Knowledge graph

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Cultivating Cluster Enactment in Wireless Sensor Networks Through Hybrid Metaheuristics Intended for Energy Optimization

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SN computer science 2025年第3期6卷 1-12页

作者： Kushwaha, Ajay Goswami, Anjali Sharada, K. Sharma, Manmohan Berar, Gagandeep Edara, Deepak Chowdary Department of Computer Science and Engineering Rungta College of Engineering and Technology R1 CG Bhilai India Department of Mathematics and Statistics College of Science and Theoretical Studies Saudi Electronic University Riyadh 13323 Saudi Arabia Department of Computer Science and Engineering GITAM (Deemed to be University) AP Visakhapatnam India Department of Computer Science and Engineering Manipal University Jaipur Rajasthan Jaipur India Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of CSE Vignan’s Foundation for Science Technology and Research Vadlamudi AP Guntur India

Though traditional search methods shine when faced with local goals and a plethora of decision factors, they could struggle when faced with engineering design limitations. On the other hand, metaheuristic approaches promise to find global optima in real-world optimization problems, even in nonlinear and multimodal settings. In order to improve cluster head selection in Wireless Sensor Networks (WSNs), this research presents a new metaheuristic method that combines the principles of Cuckoo Search method (CSA) and Selection by Optimization (SBO). When choosing a Chief Cluster Head (CCH), the CSA algorithm takes hop count into account, whereas SBO finds the best cluster heads by considering communication range. By comparing the suggested approach to both stand-alone SBO and CSA methods, we can see how well it performs in terms of throughput, latency, energy usage, delivery ratio, and packet overhead. The combined SBO-CSA method improves cluster performance, simplifies cluster head selection in WSNs, and increases network efficiency overall, according to the results. To prove its efficacy in enhancing network performance, the suggested solution outperforms standalone SBO and CSA approaches across a range of performance parameters, such as throughput, latency, energy consumption, and packet overhead. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： CCH CH CSA Metaheuristic methods SBO

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