Biometric Recognition
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Home > Computing and Information Technology > Computer science > Artificial intelligence > Pattern recognition > Biometric Recognition: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings(16360 Lecture Notes in Computer Science)
Biometric Recognition: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings(16360 Lecture Notes in Computer Science)

Biometric Recognition: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings(16360 Lecture Notes in Computer Science)


     0     
5
4
3
2
1



Out of Stock


Notify me when this book is in stock
X
About the Book

LNCS 16360 constitutes the proceedings of the 19th Chinese Conference on Biometric Recognition, CCBR 2025, held in Nanchang, China, during November 21–23, 2025. The 62 full papers presented here were carefully reviewed and selected from 90 submissions. They were organized in the following topical sections: Fingerprint, Palmprint and Vein Recognition; Human-Centric AIGC (Face Synthesis, Speech Synthesis, Gesture Generation, Human Motion Generation, etc.); Gait, Footprint;  Face Related; Emotional, Psychological, Physiological, and Health Intelligence Perception and Computing; Biometrics in Mobile Terminals, Healthcare, Banking, Internet of Things, Self-Driving,  Intelligent Robots, etc; Anti-spoofing, Presentation Attack Detection; Human-Related Understanding; Basic Theory of Biometric Recognition; Gesture, Action; Individual Characterization and Human-Computer Interaction; Adversarial Attack and Proactive Defense; Adversarial Attack and Proactive Defense; Template Protection and Cryptosystems; Datasets, Evaluation, Benchmarking, Performance Modelling and Prediction; Others.

Table of Contents:
.- Fingerprint, Palmprint and Vein Recognition. .- EC-PVGAN : Affine-Equivariant Generative Adversarial Data Augmentation for Palm-Vein Identification. .- A cloud-edge-end federated learning secret sharing scheme for finger vein recognition system. .- Toward Abandoning Tedious ROI Alignment for Unconstrained Palmprint Recognition. .-  Contact-to-Contactless Fingerprint Generation with Content Consistency. .- UMR-Net: Unified Multimodal Representation Network for Multimodal Biometric Recognition with Missing Modality. .- Enhanced Contactless Palmprint Backdoor Attack with Invisible Sample-Specific Triggers. .-  Progressive Adversarial Learning for Multi-Modality Biometric Recognition with Missing Modality. .- Learning Without Borders: A Domain-Adapted and Federated Approach to Palmprint Recognition. .- Cross-Domain Palmprint Cryptosystems via Image Alignment and Neural Error Correction. .- TSCAN: Teacher-Student Co-Learning Adaptive Network for Cross-Device Palmprint Recognition. .- Internal Fingerprint Imaging System Based On Full Field Optical Coherence Tomography. .- AReview on Palmprint Image-level Attacks. .- Topographic Feature-Based Vein Biometric Recognition. .- RSANet Multi-level Fusion Dual-modal Recognition Network. .- Dynamic Selective Distillation Network Based on Quality-Aware Fusion for Multimodal Biometric Recognition LACE: LearnableAdaptive Cross-Entropy Loss for vein recognition  .- Human-Centric AIGC (Face Synthesis, Speech Synthesis, Gesture Generation, Human Motion Generation, etc.). .- EmoPrompt+: Emotional Image Content Generation via Emotion-Driven Prompting and Multi-Level Emotional Guidance in Stable Diffusion. .- Online Emotion-Driven Generation of Multiple Appropriate Facial Reactions. .- HairEditor: Diffusion-Guided Supervision for StyleGAN-Based Hair Editing in Real-World Portraits. .- Conservation-informed Neural Network for Human Motion Prediction. .- High-Low Feature Fusion Generative Adversarial Network for the Inpainting of Irregularly Occluded Iris Images. .- FP-Director: Direction-Guided Latent Code Refinement for Facial-Preference Alignment in Text-to-Image Diffusion. .- Hand Motion Retargeting Based on GraphAttention Residual Perception. .- Gait, Footprint. .- SMEGNet:ALightweight MLP-EnhancedArchitecture for Cross-View Gait Recognition. .- Revisiting Euclidean Triplet Loss for Gait Recognition. .- Action-agnostic Pose-based Gait Recognition. .- DeepSNNGait:ASpiking Neural Network Framework for Robust Gait Recognition. .- HealthGait-Uni: Health Assessment by Human Body Appearance and Motion from  Videos. .- Face Related. .- DRAge: Dynamic Routing Mixture of Experts for Facial Age Estimation. .- PGS-Net: Personalized Graph Structure Network with Self-Supervised Learning for Micro-Expression Recognition. .- Cross-Paradigm Facial Expression Recognition based Emotional Category-Feature Prototypes. .- Attribute-Driven Identity Disentanglement for Fine-Grained Face Anonymization. .-  Emotional, Psychological, Physiological, and Health Intelligence Perception and Computing. .- AU-LLM: Micro-ExpressionAction Unit Detection via Enhanced LLM-Based Feature Fusion.  .- TwoM:An EEG depression identification model via spatiotemporal filtering. .- Learning to Decompose and Fuse A Hybrid Approach for Noise-Robust Remote Photoplethysmography. .- Automatic Sleep Stage Classification with Hypergraph Neural Networks Using Spatial-Temporal Features. .- Biometrics in Mobile Terminals, Healthcare, Banking, Internet of Things, Self-Driving, Intelligent Robots, etc. .- Research on DNA storage encoding methods and evaluation standard system .- MSPD-SAM: A Prompt-Free Framework for Cardiac Segmentation using Multi-Scale Adapters and Parallel Decoding. .- MGONet:An Optimized Segmentation Network for Esophageal Cancerous Lesions. .- Automatic Assessment of Facial Paralysis Severity from 3D Point Clouds. .- AM-UNet:Attention Mamba U-Net for Medical Image Segmentation. .- Multi-scale Channel Attention Vision LSTM Network for Optic Cup and Optic Disc Segmentation. .- Anti-spoofing, Presentation Attack Detection. .- Deep Learning-Based Approaches for Iris Image Spoofing Prevention and Tamper Detection. .- Fingerprint Liveness Detection Based on EfficientNet andAdversarial attacks. .- Bridging Synthetic and Real Domains for Face Presentation Attack Detection via Entropy-Regularized Alignment. .-  Adapting Vision Transformer with Dual Stream Token Difference for Mobile Face Anti-Spoofing. .- Domain Generalization in Face Anti-Spoofing based on Vision-Language Semantic Awareness. .- Human-Related Understanding. .- Distribution-discriminative and Modality-aware Test-time Cross-domain Adaptation for Text-based Person Search. .- MFNet: Mamba-Driven Feature Fusion for Human Parsing. .- Automatic Visual-Language Aligning Network for Visible-Infrared Person Re-Identification. .- Temporally-Aware Multi-task Representation Learning for Compositional Action Recognition. .- CGDRF-YOLO:Alightweight and efficient UAV-based pedestrian detection algorithm. .- Region-level Cross-modal Matching Framework for Text-based Geo-localization. .- Basic Theory of Biometric Recognition. .- Exponential Non-negative Matrix Factorization for Image Data Representation. .- Orthogonal-Bidirectional Pose Anchoring Model for Micro-Expression Recognition. .- Gesture, Action. .-  A Unified Transformer with a Parametric Activation Function for Robust Gesture Recognition across Sparse and Dense EMG Signals. .- Multimodal Higher-Order Statistical Adapter For Video Action Recognition. .- Individual Characterization and Human-Computer Interaction. .- Context- and Visibility-Aware Part Learning for Aerial-Ground Person Re-Identification. .- Adversarial Attack and Proactive Defense. .-  Adversarial Prompt Increment for Robust Vision-Language Models. .- Template Protection and Cryptosystems. .- A highly secure biometric template protection method based on Householder matrices and Absolute Value Equation Transform. .- Datasets, Evaluation, Benchmarking, Performance Modelling and Prediction. .- Study on the Construction of a Biometric Database of Parasites in Cattle and Sheep. .- Others. .- Disentangled Representation Learning for Single-Domain Generalization in PPG Biometric Recognition.


Best Sellers


Product Details
  • ISBN-13: 9789819561223
  • Publisher: Springer Verlag, Singapore
  • Publisher Imprint: Springer Verlag, Singapore
  • Height: 235 mm
  • No of Pages: 598
  • Returnable: N
  • Returnable: N
  • Returnable: N
  • Returnable: N
  • Series Title: 16360 Lecture Notes in Computer Science
  • Width: 155 mm
  • ISBN-10: 9819561221
  • Publisher Date: 28 Jan 2026
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Returnable: N
  • Returnable: N
  • Returnable: N
  • Returnable: N
  • Sub Title: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Biometric Recognition: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings(16360 Lecture Notes in Computer Science)
Springer Verlag, Singapore -
Biometric Recognition: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings(16360 Lecture Notes in Computer Science)
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Biometric Recognition: 19th Chinese Conference, CCBR 2025, Nanchang, China, November 21–23, 2025, Proceedings(16360 Lecture Notes in Computer Science)

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    Fresh on the Shelf


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!