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[null,"1.","Record Nr.",null,"UNISALENTO991001658649707536"]
[null,null,"Autore",null,"Sieben, Hermann Josef"]
[null,null,"Titolo",null,"Voces : eine Bibliographie zu Wörtern und Begriffen aus der Patristik (1918-1978) / Hermann Josef Sieben"]
[null,null,"Pubbl/distr/stampa",null,"Berlin ; New York : de Gruyter, 1980"]
[null,null,"ISBN",null,"3110079666"]
[null,null,"Descrizione fisica",null,"[5], 461 p. ; 24 cm"]
[null,null,"Collana",null,"Bibliographia patristica : Supplementum ; 1"]
[null,null,"Soggetti",null,"Letteratura cristiana antica - Bibliografia"]
[{"$nulls":4},"Patristica - Bibliografia"]
[null,null,"Lingua di pubblicazione",null,"Tedesco"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Contiene indici"]
[null,"2.","Record Nr.",null,"UNINA9910512174203321"]
[null,null,"Titolo",null,"Advances in Visual Computing : 16th International Symposium, ISVC 2021, Virtual Event, October 4-6, 2021, Proceedings, Part II / / edited by George Bebis, Vassilis Athitsos, Tong Yan, Manfred Lau, Frederick Li, Conglei Shi, Xiaoru Yuan, Christos Mousas, Gerd Bruder"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021"]
[null,null,"ISBN",null,"3-030-90436-9"]
[null,null,"Edizione",null,"[1st ed. 2021.]"]
[null,null,"Descrizione fisica",null,"1 online resource (555 pages)"]
[null,null,"Collana",null,"Image Processing, Computer Vision, Pattern Recognition, and Graphics, , 3004-9954 ; ; 13018"]
[null,null,"Disciplina",null,"006.6"]
[null,null,"Soggetti",null,"Pattern recognition systems"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Engineering and Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Keynote Talks -- Embodied Perception in-the-Wild -- Design Tools for Material Appearance -- Guidance-Enriched Visual Analytics: Challenges and Opportunities -- Learning and Accruing Knowledge over Time Using Modular Architectures -- Combining Brain-Computer Interfaces and Virtual Reality: Novel 3D Interactions and Promising Applications -- Direct Estimation of Appearance Models for Image Segmentation -- Contents - Part II -- Contents - Part I -- ST: Medical Image Analysis -- Video-Based Hand Tracking for Screening Cervical Myelopathy -- 1 Introduction -- 2 Related Work -- 2.1 Development of Medical Treatments for Cervical Myelopathy -- 2.2 Expansion of 10-Second Grip and Release Test -- 2.3 Automatic Screening Methods for Various Diseases -- 3 Method Design -- 3.1 Recording Grip and Release Test -- 3.2 Image Processing -- 3.3 Pre-processing of the Data -- 3.4 Two-"]
[{"$nulls":4},"Class Classification -- 4 Experiments -- 4.1 Overview -- 4.2 Validation for Each Finger and Feature Value -- 4.3 Validation for the Selected Components -- 5 Discussion -- 5.1 Consideration of Validation Results -- 5.2 Comparison with Other Screening Methods -- 5.3 Limitations and Future Work -- 6 Conclusion -- References -- NeoUNet: Towards Accurate Colon Polyp Segmentation and Neoplasm Detection -- 1 Introduction -- 2 Related Work -- 3 Polyp Segmentation and Neoplasm Detection -- 4 NeoUNet -- 4.1 Architecture -- 4.2 Loss Function -- 5 Experiments and Discussion -- 5.1 Benchmark Dataset -- 5.2 Experiment Setup -- 5.3 Results and Discussion -- 6 Conclusion -- References -- Patch-Based Convolutional Neural Networks for TCGA-BRCA Breast Cancer Classification -- 1 Introduction -- 2 Related Literature -- 3 Methodology -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Patch Extraction -- 3.4 Patch Filtering -- 3.5 Patch Classification -- 3.6 Patch Aggregation."]
[{"$nulls":4},"3.7 Dataset Augmentation -- 4 Results and Discussion -- 4.1 Whole Slide Image Classification -- 4.2 Patch-Level and Slide-Level Classification After Grid Approach -- 4.3 Patch-Level and Slide-Level Classification After Nuclei-Guided Filtering -- 4.4 Voting Methods -- 4.5 Comparison to Related Studies -- 5 Conclusions -- References -- CT Perfusion Imaging of the Brain with Machine Learning -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Dataset -- 2.3 Pre-processing -- 2.4 Training and Deployment -- 3 Experiments -- 4 Discussion -- 5 Conclusion -- References -- Analysis of Macular Thickness Deviation Maps for Diagnosis of Glaucoma -- 1 Introduction -- 2 Methods -- 2.1 Macular OCT Imaging -- 2.2 Macular Deviation Map Processing -- 2.3 Dataset Overview -- 2.4 Machine Learning for Feature Evaluation -- 3 Results and Discussions -- 4 Conclusions -- References -- Pattern Recognition -- Variational Conditional Dependence Hidden Markov Models for Skeleton-Based Action Recognition -- 1 Introduction -- 2 Proposed Model -- 2.1 Model Definition -- 2.2 Model Training -- 2.3 Inference -- 3 Experimental Evaluation -- 3.1 Experimental Details -- 3.2 Parameter Initialization and Hyperparameter Selection -- 3.3 States, Mixtures and Temporal Dependencies -- 3.4 Experimental Results -- 3.5 Missing Values -- 4 Conclusions -- References -- The Unreasonable Effectiveness of the Final Batch Normalization Layer -- 1 Introduction -- 2 Background -- 3 Previous Findings and Existing Hypotheses -- 3.1 Adding a Final Batch Norm Layer Before the Output Layer -- 3.2 Experimentation on PlantVillage Dataset Subject to Different Configurations -- 3.3 Derived Hypotheses -- 4 Implementation Details and Experimental Results -- 4.1 Removing the Additional BN Layer During Inference (H-1) -- 4.2 Impact Level Regarding the Imbalance Ratio (H-2) and the Batch Size (H-3)."]
[{"$nulls":4},"4.3 Experimentation on the MNIST Dataset: The Impact of Final BN Layer in Basic CNNs and FC Networks [(H-4),(H-5),(H-6)] -- 5 Discussion -- 6 Conclusions -- References -- Video Analysis and Event Recognition -- Cross Your Body: A Cognitive Assessment System for Children -- 1 Introduction -- 2 Related Work -- 3 Data Acquisition and Protocol Definition -- 4 System Definition -- 4.1 Feature Extraction -- 4.2 Action Segmentation -- 4.3 Analysis -- 4.4 Conclusion -- References -- Privacy-Aware Anomaly Detection Using Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Custom Feature Methods -- 2.2 Deep Learning Methods -- 2.3 Object-Centric Methods -- 2.4 Privacy Preserving Anomaly Detection -- 3 The Proposed System -- 3.1 Segmentation Model Comparison -- 3.2 Quantitative Comparison of Models -- 3.3 Segmentation Results -- 3.4 Processing -- 4 Results and Discussion -- 4.1 Anomaly Detection "]
[{"$nulls":4},"Evaluation Metrics -- 4.2 Global Accuracy -- 4.3 Anomaly Specific Accuracy -- 5 Conclusion -- References -- Learning Self-supervised Audio-Visual Representations for Sound Recommendations -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 4 Self-supervised Audio-Visual Representation Learning -- 4.1 Baseline Model -- 4.2 Attention-Based Model -- 4.3 Unlabeled Contrastive Learning -- 5 Performance Evaluation -- 5.1 Audio-Visual Correlation Performance -- 5.2 Sound Recommendation Performance -- 6 Conclusions -- References -- Poster -- Security Automation Through a Multi-processing Real-Time System for the Re-identification of Persons -- 1 Introduction -- 2 Background -- 2.1 Person Detection and Tracking -- 2.2 Person Re-identification -- 3 Research Methodology -- 3.1 Prototype Pipeline -- 3.2 Datasets -- 3.3 Person Detection and Tracking -- 3.4 Vehicle Detection and Assignment -- 3.5 Clothes Detection -- 3.6 Clothes Color Detection."]
[{"$nulls":4},"3.7 Histogram Processing and Correlation Metrics -- 3.8 Final Stage - Re-identification Using Multiple Features -- 3.9 Ethical Considerations -- 4 Findings and Discussion of Results -- 4.1 Single Person Comparison from 2 Separate Feeds -- 4.2 Multiple Persons Comparison from 2 Separate Feeds -- 5 Conclusion -- References -- A Method for Transferring Robot Motion Parameters Using Functional Attributes of Parts -- 1 Introduction -- 2 Problem Formulation -- 3 Parts Function -- 3.1 ``Part Functions'' of Industrial Parts -- 3.2 Robot Motion Parameters for Assembly -- 3.3 Basic Idea of Proposed Method Regarding Functional Attributes of Parts -- 4 Proposed Method for Transferring Robot Motion Parameters -- 4.1 Module for Functional-Attribute Recognition -- 4.2 Module for Transferring of Grasping and Action Points -- 4.3 Transferring Operating Pattern -- 5 Experiments on Transferring Robot Motion Parameters -- 5.1 Setup -- 5.2 Experimental Results -- 6 Conclusion -- References -- Uncooperative Satellite 6D Pose Estimation with Relative Depth Information -- 1 Introduction -- 2 Related Works -- 3 Approach -- 3.1 Image Simulation -- 3.2 Network Architecture -- 4 Experiment -- 5 Conclusion and Future Work -- References -- Non-homogeneous Haze Removal Through a Multiple Attention Module Architecture -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Architecture -- 3.2 Loss Functions -- 3.3 Instance Normalization -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Training Settings -- 4.3 Comparisons -- 5 Conclusions -- References -- Vehicle Detection and Tracking from Surveillance Cameras in Urban Scenes -- 1 Introduction -- 2 Background and Related Works -- 3 Proposed Solution -- 4 Results and Discussion -- 5 Conclusion -- References -- Towards the Creation of Spontaneous Datasets Based on Youtube Reaction Videos -- 1 Introduction -- 2 Related Work."]
[{"$nulls":4},"3 Proposed Method -- 3.1 Obtaining Data -- 3.2 Pre-processing and Frames Extraction -- 3.3 Faces and Facial Landmarks Extraction -- 3.4 Most Intense Moment (MIM) -- 3.5 Facial Emotion Recognition -- 3.6 Emotion Recognition Analysis -- 3.7 Dataset Generated -- 4 Final Considerations -- References -- Automated Bite-block Detection to Distinguish Colonoscopy from Upper Endoscopy Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Image Preprocessing -- 3.2 Bite-block CNN and Tongue CNN -- 3.3 Classifications of Bite-block and Tongue Patches -- 3.4 Detection of Upper Endoscopy Video -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Training and Testing -- 4.3 Performance Metrics and Accuracy Comparison -- 4.4 Effects of Hue and Saturation -- 5 Conclusion -- References -- How Does Heterogeneous Label Noise Impact Generalization in Neural Nets? -- 1 Introduction -- 2 Related "]
[{"$nulls":4},"Works -- 3 Problem Setup -- 3.1 Multi-class Classification -- 3.2 Multi-task Learning -- 3.3 Multi-label Learning -- 4 Experiments and Datasets -- 4.1 Multi-class Classification -- 4.2 Multi-task Learning -- 4.3 Multi-label Learning -- 5 Results -- 5.1 Multi-class Classification -- 5.2 Multi-task Learning -- 5.3 Multi-label Learning -- 6 Discussion -- 7 Conclusion -- References -- A Simple Generative Network -- 1 Introduction -- 2 SGN Proposed Model -- 3 Simulation Results -- 4 Concluding Remarks -- References -- Hyperspectral Video Super-Resolution Using Beta Process and Bayesian Dictionary Learning -- 1 Introduction -- 1.1 Scene Geometry in Hyperspectral Imaging -- 1.2 Hyperspectral Video Registration -- 1.3 Contribution -- 1.4 Paper Organization -- 2 Related Works -- 2.1 Super-Resolution -- 2.2 Hyperspectral Image Analysis -- 2.3 Hyperspectral Image and Video Super-Resolution -- 3 Methodology -- 3.1 Spatial Super-Resolution for a Hyperspectral Video."]
[{"$nulls":4},"3.2 Spectral Video Restoration."]
[null,null,null,"Sommario/riassunto","This two-volume set of LNCS 13017 and 13018 constitutes the refereed proceedings of the 16th International Symposium on Visual Computing, ISVC 2021, which was held in October 2021. The symposium took place virtually instead due to the COVID-19 pandemic. The 48 papers presented in these volumes were carefully reviewed and selected from 135 submissions. The papers are organized into the following topical sections: Part I: deep learning; computer graphics; segmentation; visualization; applications; 3D vision; virtual reality; motion and tracking; object detection and recognition. Part II: ST: medical image analysis; pattern recognition; video analysis and event recognition; posters."]