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[null,"1.","Record Nr.",null,"UNISA996500066503316"]
[null,null,"Titolo",null,"Biometric recognition : 16th Chinese conference, CCBR 2022, Beijing, China, November 11-13, 2022, proceedings / / Weihong Deng [and seven others]"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-20233-3"]
[null,null,"Descrizione fisica",null,"1 online resource (711 pages)"]
[null,null,"Collana",null,"Lecture notes in computer science ; ; Volume 13268"]
[null,null,"Disciplina",null,"006.4"]
[null,null,"Soggetti",null,"Biometric identification"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Fingerprint, Palmprint and Vein Recognition -- A Finger Bimodal Fusion Algorithm Based on Improved Densenet -- 1 Introduction -- 2 Research Backgrounds -- 2.1 Multimodal Fusion Strategy -- 2.2 DenseNet161 -- 3 Methodology -- 3.1 Overview -- 3.2 SENET -- 3.3 Loss Function -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Experimental Results -- 5 Conclusion -- References -- A Lightweight Segmentation Network Based on Extraction -- 1 Introduction -- 2 Method -- 2.1 TRUnet Network -- 2.2 Building the Lightformer Mechanism -- 2.3 Building the Global-Lightweight Module -- 3 Experiment and Analysis -- 3.1 Data Pre-processing -- 3.2 Experimental Environment -- 3.3 Network Performance Evaluation Index -- 3.4 Network Experiment Comparison -- 3.5 Model Visualization -- 4 Conclusion -- References -- A Novel Multi-layered Minutiae Extractor Based on OCT Fingerprints -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 The Network Architecture -- 3.2 Loss Definition -- 4 Experiments -- 4.1 Dataset and Training Protocol -- 4.2 Effectiveness of SECFMENet -- 4.3 Comparisons -- 5 Conclusion and Future Work -- References -- An Overview and Forecast of Biometric Recognition Technology Used in Forensic Science -- 1 Introduction -- 2 Traces for Biometric Recognition that Are Left at a Crime Scene, Such as Fingerprints -- 3 DNA Sequence Information of Hereditary Materials, Such as the STR Locus -- 4 Biological Characteristics Relying on Machine Recognition, Such as Portraits and Voiceprints -- 5 New Biometric Recognition Technology Such as Gait and Long-Distance Iris Recognition -- 6 "]
[{"$nulls":4},"Summary and Prospects for Biometric Recognition Technology in Forensic Analysis -- References -- Combining Band-Limited OTSDF Filter and Directional Representation for Palmprint Recognition -- 1 Introduction."]
[{"$nulls":4},"2 Brief Review of BLPOC -- 3 The Proposed BLOTSDF Filter -- 4 Combining BLOTSDF and DR for Palmprint Recognition -- 5 Experiments -- 5.1 Databases and Experimental Environment -- 5.2 Performance Evaluation on PolyU II Database -- 5.3 Performance Evaluation on PolyU MB Database -- 6 Conclusions -- References -- Cross-dataset Image Matching Network for Heterogeneous Palmprint Recognition -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Style Alignment -- 3.2 Global Reasoning -- 4 Experiments -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Experiment Results -- 4.4 Compare with Other Palmprint Recognition Methods -- 5 Conclusion -- References -- Dual Mode Near-Infrared Scanner for Imaging Dorsal Hand Veins -- 1 Introduction -- 2 The Related Work -- 3 Design Scheme of MultiVein -- 3.1 Architecture and Actual Hardware Design of MultiVein -- 3.2 The Driving Design of the Backlight LED Array -- 4 Experiments and Image Quality Assessment -- 4.1 Image Acquisition Experiments -- 4.2 Qualitative Evaluation of Image Quality -- 4.3 Quantitative Evaluation of Image Quality -- 5 Conclusions -- References -- Multi-stream Convolutional Neural Networks Fusion for Palmprint Recognition -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Multi-stream CNNs Fusion Framework -- 3.2 Three-Stream CNNs Fusion for Palmprint Recognition -- 4 Experiments -- 4.1 Palmprint Databases and Experimental Configuration -- 4.2 Experiments of Different Values of p in MFRAT -- 4.3 Experimental Results on Five Databases -- 5 Conclusions -- References -- Multi-view Finger Vein Recognition Using Attention-Based MVCNN -- 1 Introduction -- 2 Proposed Method -- 2.1 Multi-view Imaging Approaches -- 2.2 Multi-view Recognition Network -- 3 Experiments -- 3.1 Experimental Settings -- 3.2 Single-view Recognition Experiments -- 3.3 Multi-view Recognition Comparison Experiments."]
[{"$nulls":4},"4 Conclusion -- References -- Selective Detail Enhancement Algorithm for Finger Vein Images -- 1 Introduction -- 2 Relevant Work -- 2.1 Guided Filtering -- 2.2 Weighted Guided Filtering -- 3 Selective Detail Enhancement Algorithm for Finger Vein Images -- 3.1 Weighted Guided Filtering Improved by Gradient Operator -- 3.2 Selective Detail Enhancement -- 4 Experimental Results and Analysis -- 4.1 Experimental Environment -- 4.2 Analysis of Venous Enhancement Effect -- 4.3 Comparison Experiment of Recognition Rate -- 5 Conclusion -- References -- SP-FVR: SuperPoint-Based Finger Vein Recognition -- 1 Introduction -- 2 Proposed Method -- 2.1 Pre-processing -- 2.2 Keypoint Extraction and Description -- 2.3 Matching -- 3 Experimental Results -- 3.1 Experimental Databases -- 3.2 Evaluation Protocols -- 3.3 Performance Analysis -- 3.4 Comparison with State-of-the-Art Keypoint-Based Methods -- 4 Conclusion and Discussion -- References -- TransFinger: Transformer Based Finger Tri-modal Biometrics -- 1 Introduction -- 2 Related Work -- 2.1 Finger Unimodal Biometrics -- 2.2 Finger Multi-modal Biometrics -- 3 Transformer Based Fusion and Recognition Framework -- 3.1 Transformer Attention -- 3.2 TransFusion -- 4 Simulation Results -- 5 Conclusion -- References -- Face Detection, Recognition and Tracking -- A Survey of Domain Generalization-Based Face Anti-spoofing -- 1 Introduction -- 2 Methodologies -- 2.1 Domain Alignment-Based Methods -- 2.2 Meta-Learning-Based Methods -- 2.3 Disentangled Representation Learning-Based Methods -- 2.4 Others -- 3 Datasets "]
[{"$nulls":4},"and Evaluation -- 4 Future Research Directions -- 5 Conclusion -- References -- An Empirical Comparative Analysis of Africans with Asians Using DCNN Facial Biometric Models -- 1 Introduction -- 2 Related Work -- 2.1 Racial Bias Studies -- 2.2 DCNN Models -- 3 The Study."]
[{"$nulls":4},"3.1 Database Generation and Pre-processing -- 3.2 The Models -- 3.3 Dataset Visualisation -- 3.4 Face Detection Results -- 4 Conclusion -- References -- Disentanglement of Deep Features for Adversarial Face Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Supervised Feature Disentanglement -- 3.2 Detection on Predictive Inconsistency -- 4 Performance Evaluations -- 4.1 Experimental Settings -- 4.2 Adversarial Example Detection -- 4.3 Face Forgery Detection -- 5 Conclusion -- References -- Estimation of Gaze-Following Based on Transformer and the Guiding Offset -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Gaze Pathway -- 3.2 Gaze Field -- 3.3 Heatmap Pathway -- 3.4 Training -- 4 Experiments -- 4.1 Dataset and Evaluation Metric -- 4.2 Performance -- 4.3 Ablation Study -- 4.4 Analysis -- 5 Conclusion -- References -- Learning Optimal Transport Mapping of Joint Distribution for Cross-scenario Face Anti-spoofing -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Discrete Optimal Transport with Entropy Regularization -- 3.2 Learning Optimal Transport of Joint Distributions for FAS -- 4 Experimental Results -- 4.1 Databases -- 4.2 Experimental Setting -- 4.3 Experimental Results -- 5 Conclusion -- References -- MLFW: A Database for Face Recognition on Masked Faces -- 1 Introduction -- 2 Mask Tool -- 2.1 Main Procedure -- 2.2 Generation Variety -- 3 MLFW Database -- 4 Baseline -- 5 Conclusion -- References -- Multi-scale Object Detection Algorithm Based on Adaptive Feature Fusion -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Network Framework -- 3.2 PIFM Framework -- 3.3 FREM Framework -- 4 Experiment -- 4.1 Experimental Results -- 4.2 Experimental Results -- 4.3 Ablation Experiment -- 5 Conclusion -- References."]
[{"$nulls":4},"Sparsity-Regularized Geometric Mean Metric Learning for Kinship Verification -- 1 Introduction -- 2 Proposed Method -- 2.1 Notations -- 2.2 GMML -- 2.3 Sparsity Regularization -- 2.4 SGMML -- 3 Experiments -- 3.1 Datasets and Settings -- 3.2 Results and Analysis -- 4 Conclusion -- References -- YoloMask: An Enhanced YOLO Model for Detection of Face Mask Wearing Normality, Irregularity and Spoofing -- 1 Introduction -- 2 Methodology -- 2.1 Network Structure -- 2.2 Loss Function -- 3 Experiments and Analysis -- 3.1 Dataset and Setup -- 3.2 Performance Evaluation -- 4 Summary -- References -- Gesture and Action Recognition -- Adaptive Joint Interdependency Learning for 2D Occluded Hand Pose Estimation -- 1 Introduction -- 2 Occluded Hand Pose Estimation Network -- 2.1 Overview of the Occluded Hand Pose Estimation Network -- 2.2 Hand-limb Masks Learning Sub-network -- 2.3 Adaptive Joint Interdependency Learning Sub-network -- 2.4 Loss Function -- 3 Experiment -- 3.1 Dataset Settings -- 3.2 Estimation Results -- 4 Conclusion -- References -- Contrastive and Consistent Learning for Unsupervised Human Parsing -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Overall Framework -- 3.2 Part Contrastive Module -- 3.3 Pixel Consistent Module -- 3.4 Pseudo Code of C2L -- 4 Experiments -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details and Baseline -- 4.3 Ablation Study -- 4.4 Comparison on Unsupervised Human Parsing -- 5 Conclusion -- References -- Dynamic Hand Gesture Authentication Based on Improved Two-Stream CNN -- 1 Introduction -- 2 The Proposed Method -- 2.1 Analyses of the Two Stream CNN-Based DHG "]
[{"$nulls":4},"Authentication Method -- 2.2 Improved Two-Stream CNN -- 2.3 Two-Stream Information Fusion -- 3 Experiments -- 3.1 Dataset and Settings -- 3.2 Implementation Details -- 3.3 Performance of the Two Single Streams."]
[{"$nulls":4},"3.4 Impact of Local Feature Number."]