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| Titolo: |
Computer analysis of images and patterns : 19th international conference, CAIP 2021, virtual event, September 28-30, 2021, proceedings, part I / / Nicolas Tsapatsoulis [and four others], editors
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| Pubblicazione: | Cham, Switzerland : , : Springer, , [2021] |
| ©2021 | |
| Descrizione fisica: | 1 online resource (516 pages) |
| Disciplina: | 006.37 |
| Soggetto topico: | Computer vision |
| Machine learning | |
| Persona (resp. second.): | TsapatsoulisNicolas <1969-> |
| Nota di contenuto: | Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- 3D Vision -- Simultaneous Bi-directional Structured Light Encoding for Practical Uncalibrated Profilometry -- 1 Introduction -- 2 Related Work -- 3 Mathematical Investigation -- 3.1 Background: Sinusoidal Phase Shifting Method -- 3.2 Amplitude of Superposition -- 3.3 Combined Patterns -- 3.4 Mathematical Solution to the Problem -- 4 Application to Real World -- 4.1 Swapping Step -- 5 Evaluation -- 6 Conclusions -- References -- Joint Global ICP for Improved Automatic Alignment of Full Turn Object Scans -- 1 Introduction -- 2 Related Work -- 3 Background: Rigid Point Cloud Alignment -- 3.1 Orthogonal Procrustes Problem -- 3.2 Iterative Closest Point (ICP) -- 3.3 Full Turn Registration: Pulli's Approach -- 4 Joint Rigid Point Cloud Alignment -- 5 Outlier Rejection -- 6 Evaluation -- 6.1 Stopping Criterion -- 7 Conclusion -- References -- Fast Projector-Driven Structured Light Matching in Sub-pixel Accuracy Using Bilinear Interpolation Assumption -- 1 Introduction -- 2 Related Work -- 3 Fast Projector Driven Matching (FPDM) -- 3.1 Matching Integer Pixel Quads -- 3.2 Topological Consistency Check (TCC) -- 4 Bilinear Sub-pixel Matching -- 4.1 Sub-pixel Position in Unit Patch -- 4.2 Mapping to Convex Quad -- 5 Results -- 6 Conclusions -- References -- Pyramidal Layered Scene Inference with Image Outpainting for Monocular View Synthesis -- 1 Introduction -- 2 Proposed Method -- 2.1 Outpainting -- 2.2 Pyramidal Network Architecture -- 3 Results -- 4 Conclusions -- References -- Out of the Box: Embodied Navigation in the Real World -- 1 Introduction -- 2 Related Work -- 3 Real-World Navigation with Habitat -- 3.1 Baseline Architecture -- 3.2 Training in Simulation -- 3.3 LoCoNav: Adapting for Real World -- 4 Experiments -- 5 Conclusion -- References. |
| Toward a Novel LSB-based Collusion-Secure Fingerprinting Schema for 3D Video -- 1 Introduction -- 2 Related Work -- 2.1 Overview on the Existing 3D Video Watermarking Techniques -- 2.2 The Tracing Traitor: A Brief Review -- 3 The General Tracing System -- 3.1 The Copyright Registration Step -- 3.2 The Collusion Attacks -- 3.3 The Copyright Identification Step -- 4 The Proposed Traitor Tracing Framework -- 4.1 The Proposed Copyright Registration Step -- 4.2 The Proposed Copyright Identification Scheme -- 5 Experimental Results -- 5.1 The Watermarking Results -- 5.2 The Tracing Results -- 6 Conclusions and Future Work -- References -- A Combinatorial Coordinate System for the Vertices in the Octagonal C4C8(R) Grid -- 1 Introduction -- 2 Related Work -- 2.1 The 2-Valued Labelling by Ashrafi and Loghman ch7AshrafiLsps2008 -- 2.2 The 4-Valued Coordinate System by Taghizadeh et al. ch7TaghizadehAGsps2012 -- 2.3 The 2-Valued Coordinate System by Taghizadeh et al. ch7TaghizadehAGsps2012 -- 2.4 The 3-Valued Coordinate System by Siddiqui et al. ch7SiddiquiNRIsps2016 and Naeem et al. ch7NaeemSGGsps2018 -- 2.5 The 3-Valued Coordinate System by Heydari and Taeri ch7HeydariTspsRsps2007 -- 3 The Combinatorial Coordinate System -- 3.1 Definition -- 3.2 Connection with the Cartesian Coordinates -- 3.3 Neighbors -- 4 Conversion to/from Existing Coordinate Systems -- 4.1 The 2-Valued Labelling by Ashrafi and Loghman ch7AshrafiLsps2008 -- 4.2 The 4-Valued Coordinate System by Taghizadeh et al. ch7TaghizadehAGsps2012 -- 4.3 The 3-Valued Coordinate System by Siddiqui et al. ch7SiddiquiNRIsps2016 and Naeem et al. ch7NaeemSGGsps2018 -- 4.4 The 3-Valued Coordinate System by Heydari and Taeri ch7HeydariTspsRsps2007 -- 5 Discussion -- References -- Bilingual Speech Recognition by Estimating Speaker Geometry from Video Data -- 1 Introduction -- 2 3D Speaker Geometry Estimation. | |
| 3 Methodology -- 3.1 Object Detection -- 3.2 Speech Recognition System -- 4 Results -- 5 Conclusions and Future Work -- References -- Cost-Efficient Color Correction Approach on Uncontrolled Lighting Conditions -- 1 Introduction -- 2 Previous Work -- 3 Methodology -- 3.1 Data -- 3.2 Color Correction -- 4 Results -- 5 Conclusions -- References -- HPA-Net: Hierarchical and Parallel Aggregation Network for Context Learning in Stereo Matching -- 1 Introduction -- 2 Related Work -- 2.1 Deep Neural Networks for Stereo Matching -- 2.2 Multi-scale Information -- 3 Proposed Method -- 3.1 Network Architecture -- 3.2 Hierarchical Aggregation (HA) Network -- 3.3 Parallel Aggregation (PA) Network -- 3.4 Output Module and Loss Function -- 4 Experimental Results -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Ablation Studies -- 4.4 KITTI Datasets Results -- 5 Conclusion -- References -- MTStereo 2.0: Accurate Stereo Depth Estimation via Max-Tree Matching -- 1 Introduction -- 2 MTStereo 2.0 -- 2.1 Steps Performed by MTStereo 2.0 -- 3 Experiments -- 3.1 Evaluation -- 3.2 Results and Comparison -- 4 Conclusions -- References -- Biomedical Image and Pattern Analysis -- H-OCS: A Hybrid Optic Cup Segmentation of Retinal Images -- 1 Introduction -- 2 Proposed Method -- 2.1 Region of Interest Extraction -- 2.2 Network Architecture -- 2.3 Loss Function -- 2.4 Transfer Learning -- 2.5 Postprocessing -- 3 Experimental Analysis -- 3.1 Datasets -- 3.2 Implementation Details -- 3.3 Effectiveness of TL and IA -- 3.4 Effectiveness of Loss Functions -- 3.5 Comparison with Other Approaches -- 4 Conclusion -- References -- Retinal Vessel Segmentation Using Blending-Based Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Proposed Method -- 2.1 Datasets -- 2.2 Blending and Enhancement-Based Strategy -- 2.3 GAN Synthesization. | |
| 2.4 CNN-Based Segmentation -- 3 Experimental Evaluation -- 3.1 Qualitative Result -- 3.2 Quantitative Result -- 4 Conclusion -- References -- U-Shaped Densely Connected Convolutions for Left Ventricle Segmentation from CMR Images -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Architecture -- 3.4 Post-processing -- 3.5 Evaluation Metrics -- 4 Experiments and Results -- 5 Conclusion -- References -- Deep Learning Approaches for Head and Operculum Segmentation in Zebrafish Microscopy Images -- 1 Introduction -- 2 Methodology -- 2.1 Image Acquisition and Dataset Description -- 2.2 Two Deep Learning Strategies -- 2.3 U-Net Implementation -- 2.4 Experimental Protocol -- 2.5 Model Training with Different Loss Functions -- 3 Results and Discussion -- 3.1 Robustness to Image Acquisition with Another Microscope -- 4 Conclusions -- References -- Shape Analysis Approach Towards Assessment of Cleft Lip Repair Outcome -- 1 Introduction -- 2 Method -- 2.1 Dataset and Tools -- 2.2 Feature Description and Detection -- 2.3 Symmetrical Axis Detection and Measurement -- 2.4 Conversion of Similarity Measure to a Numeric Score -- 3 Experimental Results -- 3.1 Image Segmentation -- 3.2 Evaluation of Aesthetic Assessment -- 4 Conclusion -- References -- MMEC: Multi-Modal Ensemble Classifier for Protein Secondary Structure Prediction -- 1 Introduction -- 2 Methodology -- 2.1 Convolutional Neural Networks -- 2.2 BERT -- 2.3 Inception Recurrent Networks -- 2.4 Multi-Modal Ensemble Classifier -- 2.5 Genetic Algorithm -- 3 Datasets and Evaluation Metric -- 3.1 Datasets -- 3.2 Evaluation Metric -- 4 Experimental Evaluation -- 4.1 CB6133 -- 4.2 CB513 -- 5 Conclusions and Future Work -- References -- Patch-Level Nuclear Pleomorphism Scoring Using Convolutional Neural Networks -- 1 Introduction -- 1.1 Related Work. | |
| 2 Data and Materials -- 3 Methods -- 3.1 Model Training -- 4 Experimental Set-Up -- 5 Results -- 5.1 Validation Results -- 5.2 Test Results -- 6 Discussion -- 7 Conclusion -- References -- Automatic Myelofibrosis Grading from Silver-Stained Images -- 1 Introduction -- 2 Related Work and Open Issues -- 3 Materials and Methods -- 3.1 Data Set -- 3.2 Image Classification -- 4 Experimental Evaluation -- 4.1 Experimental Set-Up -- 4.2 Results -- 5 Conclusions -- References -- A Deep Learning-Based Pipeline for Celiac Disease Diagnosis Using Histopathological Images -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Methodology -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- HEp-2 Cell Image Recognition with Transferable Cross-Dataset Synthetic Samples -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 4 Proposed Method -- 5 Evaluation and Discussion -- 6 Conclusion -- References -- Clinically Guided Trainable Soft Attention for Early Detection of Oral Cancer -- 1 Introduction -- 2 Related Work -- 3 Materials -- 4 Method -- 4.1 Attention Network -- 4.2 Guided Attention -- 4.3 Technical Details -- 5 Results -- 6 Discussion and Conclusion -- References -- Small and Large Bile Ducts Intrahepatic Cholangiocarcinoma Classification: A Preliminary Feature-Based Study -- 1 Introduction -- 2 Proposed Classification Algorithm -- 2.1 Tumor Segmentation -- 2.2 Feature Extraction -- 2.3 Feature Selection -- 3 Performance Evaluation -- 3.1 Patients Dataset -- 3.2 Classification Procedure and Results -- 4 Conclusions -- References -- A Review on Breast Cancer Brain Metastasis: Automated MRI Image Analysis for the Prediction of Primary Cancer Using Radiomics -- 1 Introduction -- 2 Literature Review -- 2.1 Image Preprocessing and Brain Metastasis Segmentation -- 2.2 Prediction of Brain Metastasis: Breast Cancer Origin -- 3 Discussion. | |
| References. | |
| Titolo autorizzato: | Computer Analysis of Images and Patterns ![]() |
| ISBN: | 3-030-89128-3 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 996464389303316 |
| Lo trovi qui: | Univ. di Salerno |
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