Pattern Recognition and Image Analysis [[electronic resource] ] : 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings / / edited by Antonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues |
Autore | Pertusa Antonio |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (735 pages) |
Disciplina | 006.4 |
Altri autori (Persone) |
GallegoAntonio Javier
SánchezJoan Andreu DominguesInês |
Collana | Lecture Notes in Computer Science |
Soggetto topico |
Pattern recognition systems
Education—Data processing Social sciences—Data processing Computer vision Machine learning Automated Pattern Recognition Computers and Education Computer Application in Social and Behavioral Sciences Computer Vision Machine Learning |
ISBN | 3-031-36616-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Machine Learning -- CCLM: Class-conditional Label Noise Modelling -- Addressing class imbalance in Multilabel Prototype Generation for k-Nearest Neighbor classification -- Time series imputation in faulty systems -- DARTS with degeneracy correction -- A fuzzy logic inference system for display characterization -- Learning Semantic-Visual Embeddings with a Priority Queue -- Learning Semantic-Visual Embeddings with a Priority Queue -- Continual vocabularies to tackle the catastrophic forgetting problem in Machine Translation -- Evaluating Domain Generalization in Kitchen Utensils Classification -- Document Analysis -- Segmentation of Large Historical Manuscript Bundles into Multi-page Deeds -- A Study of Augmentation Methods for Handwritten Stenography Recognition -- Lifelong Learning for Document Image Binarization: A Experimental Study -- Test-Time Augmentation for Document Image Binarization -- A Weakly-Supervised Approach for Layout Analysis in Music Score Images -- ResPho(SC)Net: A Zero-Shot Learning Framework for Norwegian Handwritten Word Image Recognition -- Computer Vision -- DeepArUco: Marker detection and classification in challenging lightning conditions -- Automated Detection and Identification of Olive Fruit Fly using YOLOv7 Algorithm -- Learning to search for and detect objects in foveal images using deep learning -- Relation networks for few-shot video object detection -- Optimal Wavelength Selection for Deep Learning from Hyperspectral Images -- Can representation learning for multimodal image registration be improved by supervision of intermediate layers? -- Interpretability-Guided Human Feedback During Neural Network Training -- Calibration of Non-Central Conical Catadioptric Systems from Parallel Lines -- S² -LOR: Supervised Stream Learning for Object Recognition -- Evaluation of Regularization Techniques for Transformers-Based Models -- 3D Computer Vision -- Guided depth completion using active infrared images in Time of Flight system -- StOCaMo: Online Calibration Monitoring for Stereo Cameras -- Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization -- A Measure of Tortuosity for 3D Curves: Identifying 3D beating patterns of sperm flagella -- The ETS2 Dataset, synthetic data from video games for monocular depth estimation -- Computer Vision Applications -- Multimodal Human Pose feature fusion for Gait recognition -- Proxemics-Net: automatic proxemics recognition in images -- Lightweight Vision Transformers for Face Verification in the Wild -- Py4MER: a CTC-based Mathematical Expression Recognition System -- Hierarchical Line Extremity Segmentation U-Net for the SoccerNet 2022 Calibration Challenge - Pitch Localization -- Object Localization with Multiplanar Fiducial Markers: Accurate Pose Estimation -- Real-time unsupervised object localization on the edge for airport video surveillance -- Identifying Thermokarst Lakes Using Discrete Wavelet Transform–Based Deep Learning Framework -- Object Detection for Rescue Operations by High-altitude Infrared Thermal Imaging Collected by Unmanned Aerial Vehicles -- Medical Imaging & Applications -- Inter vs. Intra Domain Study of COVID Chest X-Ray Classification with Imbalanced Datasets -- Automatic Eye-Tracking-Assisted Chest Radiography Pathology Screening -- Deep Neural Networks to distinguish between Crohn’s disease and Ulcerative colitis -- Few-shot image classification for automatic COVID-19 diagnosis -- An ensemble-based phenotype classifier to diagnose Crohn’s disease from 16s rRNA gene sequences -- Synthetic spermatozoa video sequences generation using Adversarial Imitation Learning -- A Deep Approach for Volumetric Tractography Segmentation -- MicrogliaJ: an Automatic Tool for Microglial Cell Detection and Segmentation -- Automated Orientation Detection of 3D Head Reconstructions from sMRI using Multiview Orthographic Projections: An Image Classification-Based Approach -- Machine Learning Applications -- Enhancing Transferability of Adversarial Audio in Speaker Recognition Systems -- Fishing Gear Classification from Vessel Trajectories and Velocity Profiles: Database and Benchmark -- Multi-view Infant Cry Classification -- Study and automatic translation of Toki Pona -- Detecting Loose Wheel Bolts of a Vehicle using Accelerometers in the Chassis -- Clustering ECG time series for the quantification of physiological reactions to emotional stimuli -- Predicting the Subjective Responses’ Emotion in Dialogues with Multi-Task Learning -- Few-shot learning for prediction of electricity consumption patterns. |
Record Nr. | UNISA-996538665603316 |
Pertusa Antonio
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Pattern Recognition and Image Analysis : 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings / / edited by Antonio Pertusa, Antonio Javier Gallego, Joan Andreu Sánchez, Inês Domingues |
Autore | Pertusa Antonio |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (735 pages) |
Disciplina |
006.4
006.42 |
Altri autori (Persone) |
GallegoAntonio Javier
SánchezJoan Andreu DominguesInês |
Collana | Lecture Notes in Computer Science |
Soggetto topico |
Pattern recognition systems
Education—Data processing Social sciences—Data processing Computer vision Machine learning Automated Pattern Recognition Computers and Education Computer Application in Social and Behavioral Sciences Computer Vision Machine Learning |
ISBN | 3-031-36616-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Machine Learning -- CCLM: Class-conditional Label Noise Modelling -- Addressing class imbalance in Multilabel Prototype Generation for k-Nearest Neighbor classification -- Time series imputation in faulty systems -- DARTS with degeneracy correction -- A fuzzy logic inference system for display characterization -- Learning Semantic-Visual Embeddings with a Priority Queue -- Learning Semantic-Visual Embeddings with a Priority Queue -- Continual vocabularies to tackle the catastrophic forgetting problem in Machine Translation -- Evaluating Domain Generalization in Kitchen Utensils Classification -- Document Analysis -- Segmentation of Large Historical Manuscript Bundles into Multi-page Deeds -- A Study of Augmentation Methods for Handwritten Stenography Recognition -- Lifelong Learning for Document Image Binarization: A Experimental Study -- Test-Time Augmentation for Document Image Binarization -- A Weakly-Supervised Approach for Layout Analysis in Music Score Images -- ResPho(SC)Net: A Zero-Shot Learning Framework for Norwegian Handwritten Word Image Recognition -- Computer Vision -- DeepArUco: Marker detection and classification in challenging lightning conditions -- Automated Detection and Identification of Olive Fruit Fly using YOLOv7 Algorithm -- Learning to search for and detect objects in foveal images using deep learning -- Relation networks for few-shot video object detection -- Optimal Wavelength Selection for Deep Learning from Hyperspectral Images -- Can representation learning for multimodal image registration be improved by supervision of intermediate layers? -- Interpretability-Guided Human Feedback During Neural Network Training -- Calibration of Non-Central Conical Catadioptric Systems from Parallel Lines -- S² -LOR: Supervised Stream Learning for Object Recognition -- Evaluation of Regularization Techniques for Transformers-Based Models -- 3D Computer Vision -- Guided depth completion using active infrared images in Time of Flight system -- StOCaMo: Online Calibration Monitoring for Stereo Cameras -- Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization -- A Measure of Tortuosity for 3D Curves: Identifying 3D beating patterns of sperm flagella -- The ETS2 Dataset, synthetic data from video games for monocular depth estimation -- Computer Vision Applications -- Multimodal Human Pose feature fusion for Gait recognition -- Proxemics-Net: automatic proxemics recognition in images -- Lightweight Vision Transformers for Face Verification in the Wild -- Py4MER: a CTC-based Mathematical Expression Recognition System -- Hierarchical Line Extremity Segmentation U-Net for the SoccerNet 2022 Calibration Challenge - Pitch Localization -- Object Localization with Multiplanar Fiducial Markers: Accurate Pose Estimation -- Real-time unsupervised object localization on the edge for airport video surveillance -- Identifying Thermokarst Lakes Using Discrete Wavelet Transform–Based Deep Learning Framework -- Object Detection for Rescue Operations by High-altitude Infrared Thermal Imaging Collected by Unmanned Aerial Vehicles -- Medical Imaging & Applications -- Inter vs. Intra Domain Study of COVID Chest X-Ray Classification with Imbalanced Datasets -- Automatic Eye-Tracking-Assisted Chest Radiography Pathology Screening -- Deep Neural Networks to distinguish between Crohn’s disease and Ulcerative colitis -- Few-shot image classification for automatic COVID-19 diagnosis -- An ensemble-based phenotype classifier to diagnose Crohn’s disease from 16s rRNA gene sequences -- Synthetic spermatozoa video sequences generation using Adversarial Imitation Learning -- A Deep Approach for Volumetric Tractography Segmentation -- MicrogliaJ: an Automatic Tool for Microglial Cell Detection and Segmentation -- Automated Orientation Detection of 3D Head Reconstructions from sMRI using Multiview Orthographic Projections: An Image Classification-Based Approach -- Machine Learning Applications -- Enhancing Transferability of Adversarial Audio in Speaker Recognition Systems -- Fishing Gear Classification from Vessel Trajectories and Velocity Profiles: Database and Benchmark -- Multi-view Infant Cry Classification -- Study and automatic translation of Toki Pona -- Detecting Loose Wheel Bolts of a Vehicle using Accelerometers in the Chassis -- Clustering ECG time series for the quantification of physiological reactions to emotional stimuli -- Predicting the Subjective Responses’ Emotion in Dialogues with Multi-Task Learning -- Few-shot learning for prediction of electricity consumption patterns. |
Record Nr. | UNINA-9910734892303321 |
Pertusa Antonio
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. Federico II | ||
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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications [[electronic resource] ] : 26th Iberoamerican Congress, CIARP 2023, Coimbra, Portugal, November 27–30, 2023, Proceedings, Part I / / edited by Verónica Vasconcelos, Inês Domingues, Simão Paredes |
Autore | Vasconcelos Verónica |
Edizione | [1st ed. 2024.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
Descrizione fisica | 1 online resource (764 pages) |
Disciplina | 006.4 |
Altri autori (Persone) |
DominguesInês
ParedesSimão |
Collana | Lecture Notes in Computer Science |
Soggetto topico |
Pattern recognition systems
Machine learning Computer vision Computer engineering Computer networks Application software Automated Pattern Recognition Machine Learning Computer Vision Computer Engineering and Networks Computer and Information Systems Applications |
ISBN | 3-031-49018-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Deblur Capsule Networks -- 1 Introduction -- 2 Related Works -- 3 Deblur Capsule Networks -- 3.1 Blur Type Classification -- 3.2 Point Spread Function Reconstruction -- 3.3 Image Deep Regularized Deconvolution -- 4 Experiments and Analysis -- 4.1 DbCN Optimization Procedure -- 4.2 Synthetic Camera Motion Blur -- 4.3 Synthetic Multi-domain Blur -- 4.4 Ablation Study -- 5 Conclusions and Future Works -- References -- Graph Embedding of Almost Constant Large Graphs -- 1 Introduction -- 2 Graphs and Graph Embedding -- 3 GraphFingerprint: An Embedding for Almost Constant Graphs -- 3.1 Algorithm Input Parameters -- 3.2 Local Substructures -- 3.3 GraphFingerprint Definition -- 3.4 GraphFingerprint Examples -- 4 Experimental Section -- 4.1 From Metal-Oxide Nanocompound to GraphFingerprint -- 4.2 Toxicity Prediction Based on Global Features -- 4.3 Toxicity Prediction Based on GraphFingerprints -- 4.4 Toxicity Prediction Based on Global Features and GraphFingerprints -- 5 Conclusions -- 6 Future Work -- References -- Feature Importance for Clustering -- 1 Introduction -- 2 Cluster Analysis -- 3 Proposed Methods -- 3.1 Prototype-Based Feature Importance -- 3.2 SHAP-Based Feature Importance -- 4 Experimental Simulations -- 5 Concluding Remarks -- References -- Uncovering Manipulated Files Using Mathematical Natural Laws -- 1 Introduction -- 2 Related Work -- 3 Benford's Law Fundamentals -- 3.1 Benford's Law Statement -- 4 Dataset -- 5 Benford's Law-Based Method -- 5.1 Pre-processing -- 5.2 Processing -- 5.3 Median Absolute Deviation -- 5.4 Evaluation Metrics -- 6 Results -- 6.1 Analysis of Results -- 7 Conclusions and Future Work -- References -- History Based Incremental Singular Value Decomposition for Background Initialization and Foreground Segmentation -- 1 Introduction.
2 Related Work -- 2.1 Identification of SFOs -- 2.2 Background Dependency -- 3 Methodology -- 3.1 Notation and Preliminaries -- 3.2 Computation of Incremental SVD -- 3.3 History Based Incremental SVD (hi-SVD) -- 4 Experimental Results -- 4.1 Datasets -- 4.2 SFO Status Identification Experiment -- 4.3 Foreground Segmentation Experiment -- 5 Conclusion -- References -- Vehicle Re-Identification Based on Unsupervised Domain Adaptation by Incremental Generation of Pseudo-Labels -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 DBSCAN Pseudo-Labels -- 3.2 Fine-Tuning -- 3.3 Unsupervised Domain Adaptation -- 4 Experimental Validation -- 4.1 Dataset and Evaluation Environment -- 4.2 Implementation Details -- 4.3 Ablation Study for Eps-Neighborhood in DBSCAN -- 4.4 Ablation Study for Increasing the Number of Cycles in the Generation of Pseudo-Labels -- 5 Conclusions -- References -- How to Turn Your Camera into a Perfect Pinhole Model -- 1 Introduction -- 2 Methods -- 2.1 Gaussian Processes -- 2.2 Constructing an Ideal Pinhole Camera -- 2.3 The Datasets -- 3 Results -- 3.1 Collineation Assumption -- 3.2 Reprojection Error -- 3.3 Distortion Removal -- 4 Discussion -- 5 Conclusion -- A Zhang's Method -- B Simplified Zhang's Method -- References -- Single Image HDR Synthesis with Histogram Learning -- 1 Introduction -- 2 Method -- 2.1 LDR2EDR by Histogram and Resolution difference -- 2.2 EDR2HDR by Cumulative Histogram Learning -- 2.3 Fine-Tuning with Reinforcement Learning -- 3 Experiments -- 4 Conclusion -- References -- But That's Not Why: Inference Adjustment by Interactive Prototype Revision -- 1 Introduction -- 2 Prototype-Based Learning -- 3 Interactive Prototype Revision -- 4 Results -- 5 Conclusion -- References -- Teaching Practices Analysis Through Audio Signal Processing -- 1 Introduction -- 2 Related Work -- 3 Dataset Description. 4 Classroom Activity Detection -- 4.1 Training and Testing Data -- 4.2 Unsupervised Diarization Approach -- 4.3 Supervised Audio Classification -- 4.4 Experiments and Results -- 5 Additional Tools for English Lessons Analysis -- 5.1 Language Detection -- 5.2 Key Phrases Matching -- 5.3 User Interface for Education Technicians -- 6 Conclusions and Further Work -- References -- Time Distributed Multiview Representation for Speech Emotion Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Strategy -- 3.1 Database Description -- 3.2 General Architecture -- 3.3 Step 1 - Initial Procedures -- 3.4 Steps 2 and 3 - Algorithms and Combiner -- 3.5 Steps 4 and 5 - LSTM and Emotion Classification -- 4 Experimental Results -- 4.1 Experiment 1 - Results for All RAVDESS Database -- 4.2 Experiment 2 - Database Divided by Intensity -- 4.3 Experiment 3 - LOSO Protocol -- 5 Discussions -- 6 Conclusion -- References -- Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Database -- 2.2 Methodology -- 3 Results and Discussion -- 3.1 Feature Evaluation -- 3.2 Performance of the HP Classifier -- 4 Conclusion -- References -- Abandoned Object Detection Using Persistent Homology -- 1 Introduction -- 2 From Background Subtraction to Simplicial Complex -- 3 Surveillance Points -- 4 Filtration -- 5 Persistent Homology and Topological Signature -- 6 Detecting Abandoned Objects -- 7 Experimental Results -- 8 Conclusion and Future Works -- References -- Interactive Segmentation with Incremental Watershed Cuts -- 1 Introduction -- 2 Watershed Cuts -- 3 Semi-supervised Watershed Cut Algorithm with Interactions -- 3.1 Tree-Node Marking -- 3.2 Pixel Labeling -- 3.3 Incremental Workflow -- 4 Experiments -- 4.1 Experiment with User Generated Seeds. 4.2 Experiment with Randomly Generated Seeds -- 5 Conclusion -- References -- Supervised Learning of Hierarchical Image Segmentation -- 1 Introduction -- 2 Ultrametric Dataset -- 3 Model -- 4 Evaluation Metrics -- 5 Experiments -- 6 Conclusion -- References -- Unveiling the Influence of Image Super-Resolution on Aerial Scene Classification -- 1 Introduction -- 2 Super-Resolution -- 2.1 Super-Resolution Convolution Neural Network (SRCNN) -- 2.2 Modified 3D Residual-in-Residual Dense Block (m3DRRDB) -- 2.3 SwinIR Transformer -- 3 Scene Classification -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 5 Results and Discussion -- 5.1 Experiment 1: Ranking of Super-Resolution Methods -- 5.2 Experiment 2: Impact of Super-Resolution on Aerial Scene Classification -- 6 Conclusion -- References -- Weeds Classification with Deep Learning: An Investigation Using CNN, Vision Transformers, Pyramid Vision Transformers, and Ensemble Strategy -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Datasets -- 3.2 Models -- 3.3 Ensemble -- 3.4 Evaluation -- 3.5 Training Configuration -- 3.6 Execution Environment -- 4 Results and Discussion -- 5 Conclusions -- References -- Leveraging Question Answering for Domain-Agnostic Information Extraction -- 1 Introduction -- 2 Related Work -- 3 Question Answering for Information Extraction -- 3.1 Models and Questions -- 3.2 Approach -- 3.3 Visual Explainability on Evaluation -- 4 Case Studies -- 4.1 Application to Toxicology Analysis -- 4.2 Application to Finance -- 5 Conclusion -- References -- Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves -- 1 Introduction -- 2 Dataset Collection -- 3 Proposed Approach -- 3.1 Image-to-Text Track -- 3.2 Localization Track -- 3.3 Selection Track -- 3.4 Report Generation -- 4 Results -- 5 Conclusions and Future Works. References -- A Self-Organizing Map Clustering Approach to Support Territorial Zoning -- 1 Introduction -- 2 Related Work -- 2.1 Zoning with Self-Organizing Maps -- 2.2 Clustering Ordinal Categorical Data -- 3 Material and Methods -- 3.1 The Alto Taquari Basin - MS/MT, Brazil -- 3.2 Clustering Categorical Ordinal Data -- 3.3 Clustering Assessing -- 4 Results and Discussion -- 5 Conclusions -- References -- Spatial-Temporal Graph Transformer for Surgical Skill Assessment in Simulation Sessions -- 1 Introduction -- 2 Proposed Approach -- 2.1 Spectral Graph Convolutional Networks -- 2.2 Transformer Encoder -- 2.3 Surgical Skill Classifier -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Results -- 4 Conclusion -- References -- Deep Learning in the Identification of Psoriatic Skin Lesions -- 1 Introduction -- 2 Background and Literature Review -- 3 Methodology -- 3.1 Understanding the Problem -- 3.2 Deep Learning -- 3.3 Dataset -- 3.4 Classification Architectures -- 3.5 Training -- 4 Results -- 4.1 CLAHE -- 4.2 Type of Input Image -- 4.3 Data Augmentation -- 5 Discussion -- 6 Mobile Application -- 7 Conclusion -- References -- WildFruiP: Estimating Fruit Physicochemical Parameters from Images Captured in the Wild -- 1 Introduction -- 2 Related Work -- 2.1 Detection Methods -- 2.2 Segmentation Methods -- 2.3 Methods for Estimating Fruit Ripeness in Images -- 3 Proposed Method -- 3.1 Fruit Detection and Segmentation -- 3.2 Image Alignment -- 3.3 Determination of Physicochemical Parameters -- 4 Dataset -- 5 Experiments -- 5.1 Implementation Details -- 5.2 Metrics -- 5.3 Performance of the Proposed Approach -- 5.4 Impact of Alignment Phase -- 5.5 Impact of Model Architecture -- 5.6 Hard Samples -- 6 Conclusion and Future Work Prospects -- References. Depression Detection Using Deep Learning and Natural Language Processing Techniques: A Comparative Study. |
Record Nr. | UNISA-996565865703316 |
Vasconcelos Verónica
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications : 26th Iberoamerican Congress, CIARP 2023, Coimbra, Portugal, November 27–30, 2023, Proceedings, Part I / / edited by Verónica Vasconcelos, Inês Domingues, Simão Paredes |
Autore | Vasconcelos Verónica |
Edizione | [1st ed. 2024.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
Descrizione fisica | 1 online resource (764 pages) |
Disciplina | 006.4 |
Altri autori (Persone) |
DominguesInês
ParedesSimão |
Collana | Lecture Notes in Computer Science |
Soggetto topico |
Pattern recognition systems
Machine learning Computer vision Computer engineering Computer networks Application software Automated Pattern Recognition Machine Learning Computer Vision Computer Engineering and Networks Computer and Information Systems Applications |
ISBN | 3-031-49018-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Deblur Capsule Networks -- 1 Introduction -- 2 Related Works -- 3 Deblur Capsule Networks -- 3.1 Blur Type Classification -- 3.2 Point Spread Function Reconstruction -- 3.3 Image Deep Regularized Deconvolution -- 4 Experiments and Analysis -- 4.1 DbCN Optimization Procedure -- 4.2 Synthetic Camera Motion Blur -- 4.3 Synthetic Multi-domain Blur -- 4.4 Ablation Study -- 5 Conclusions and Future Works -- References -- Graph Embedding of Almost Constant Large Graphs -- 1 Introduction -- 2 Graphs and Graph Embedding -- 3 GraphFingerprint: An Embedding for Almost Constant Graphs -- 3.1 Algorithm Input Parameters -- 3.2 Local Substructures -- 3.3 GraphFingerprint Definition -- 3.4 GraphFingerprint Examples -- 4 Experimental Section -- 4.1 From Metal-Oxide Nanocompound to GraphFingerprint -- 4.2 Toxicity Prediction Based on Global Features -- 4.3 Toxicity Prediction Based on GraphFingerprints -- 4.4 Toxicity Prediction Based on Global Features and GraphFingerprints -- 5 Conclusions -- 6 Future Work -- References -- Feature Importance for Clustering -- 1 Introduction -- 2 Cluster Analysis -- 3 Proposed Methods -- 3.1 Prototype-Based Feature Importance -- 3.2 SHAP-Based Feature Importance -- 4 Experimental Simulations -- 5 Concluding Remarks -- References -- Uncovering Manipulated Files Using Mathematical Natural Laws -- 1 Introduction -- 2 Related Work -- 3 Benford's Law Fundamentals -- 3.1 Benford's Law Statement -- 4 Dataset -- 5 Benford's Law-Based Method -- 5.1 Pre-processing -- 5.2 Processing -- 5.3 Median Absolute Deviation -- 5.4 Evaluation Metrics -- 6 Results -- 6.1 Analysis of Results -- 7 Conclusions and Future Work -- References -- History Based Incremental Singular Value Decomposition for Background Initialization and Foreground Segmentation -- 1 Introduction.
2 Related Work -- 2.1 Identification of SFOs -- 2.2 Background Dependency -- 3 Methodology -- 3.1 Notation and Preliminaries -- 3.2 Computation of Incremental SVD -- 3.3 History Based Incremental SVD (hi-SVD) -- 4 Experimental Results -- 4.1 Datasets -- 4.2 SFO Status Identification Experiment -- 4.3 Foreground Segmentation Experiment -- 5 Conclusion -- References -- Vehicle Re-Identification Based on Unsupervised Domain Adaptation by Incremental Generation of Pseudo-Labels -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 DBSCAN Pseudo-Labels -- 3.2 Fine-Tuning -- 3.3 Unsupervised Domain Adaptation -- 4 Experimental Validation -- 4.1 Dataset and Evaluation Environment -- 4.2 Implementation Details -- 4.3 Ablation Study for Eps-Neighborhood in DBSCAN -- 4.4 Ablation Study for Increasing the Number of Cycles in the Generation of Pseudo-Labels -- 5 Conclusions -- References -- How to Turn Your Camera into a Perfect Pinhole Model -- 1 Introduction -- 2 Methods -- 2.1 Gaussian Processes -- 2.2 Constructing an Ideal Pinhole Camera -- 2.3 The Datasets -- 3 Results -- 3.1 Collineation Assumption -- 3.2 Reprojection Error -- 3.3 Distortion Removal -- 4 Discussion -- 5 Conclusion -- A Zhang's Method -- B Simplified Zhang's Method -- References -- Single Image HDR Synthesis with Histogram Learning -- 1 Introduction -- 2 Method -- 2.1 LDR2EDR by Histogram and Resolution difference -- 2.2 EDR2HDR by Cumulative Histogram Learning -- 2.3 Fine-Tuning with Reinforcement Learning -- 3 Experiments -- 4 Conclusion -- References -- But That's Not Why: Inference Adjustment by Interactive Prototype Revision -- 1 Introduction -- 2 Prototype-Based Learning -- 3 Interactive Prototype Revision -- 4 Results -- 5 Conclusion -- References -- Teaching Practices Analysis Through Audio Signal Processing -- 1 Introduction -- 2 Related Work -- 3 Dataset Description. 4 Classroom Activity Detection -- 4.1 Training and Testing Data -- 4.2 Unsupervised Diarization Approach -- 4.3 Supervised Audio Classification -- 4.4 Experiments and Results -- 5 Additional Tools for English Lessons Analysis -- 5.1 Language Detection -- 5.2 Key Phrases Matching -- 5.3 User Interface for Education Technicians -- 6 Conclusions and Further Work -- References -- Time Distributed Multiview Representation for Speech Emotion Recognition -- 1 Introduction -- 2 Related Work -- 3 Proposed Strategy -- 3.1 Database Description -- 3.2 General Architecture -- 3.3 Step 1 - Initial Procedures -- 3.4 Steps 2 and 3 - Algorithms and Combiner -- 3.5 Steps 4 and 5 - LSTM and Emotion Classification -- 4 Experimental Results -- 4.1 Experiment 1 - Results for All RAVDESS Database -- 4.2 Experiment 2 - Database Divided by Intensity -- 4.3 Experiment 3 - LOSO Protocol -- 5 Discussions -- 6 Conclusion -- References -- Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification -- 1 Introduction -- 2 Materials and Methods -- 2.1 Image Database -- 2.2 Methodology -- 3 Results and Discussion -- 3.1 Feature Evaluation -- 3.2 Performance of the HP Classifier -- 4 Conclusion -- References -- Abandoned Object Detection Using Persistent Homology -- 1 Introduction -- 2 From Background Subtraction to Simplicial Complex -- 3 Surveillance Points -- 4 Filtration -- 5 Persistent Homology and Topological Signature -- 6 Detecting Abandoned Objects -- 7 Experimental Results -- 8 Conclusion and Future Works -- References -- Interactive Segmentation with Incremental Watershed Cuts -- 1 Introduction -- 2 Watershed Cuts -- 3 Semi-supervised Watershed Cut Algorithm with Interactions -- 3.1 Tree-Node Marking -- 3.2 Pixel Labeling -- 3.3 Incremental Workflow -- 4 Experiments -- 4.1 Experiment with User Generated Seeds. 4.2 Experiment with Randomly Generated Seeds -- 5 Conclusion -- References -- Supervised Learning of Hierarchical Image Segmentation -- 1 Introduction -- 2 Ultrametric Dataset -- 3 Model -- 4 Evaluation Metrics -- 5 Experiments -- 6 Conclusion -- References -- Unveiling the Influence of Image Super-Resolution on Aerial Scene Classification -- 1 Introduction -- 2 Super-Resolution -- 2.1 Super-Resolution Convolution Neural Network (SRCNN) -- 2.2 Modified 3D Residual-in-Residual Dense Block (m3DRRDB) -- 2.3 SwinIR Transformer -- 3 Scene Classification -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 5 Results and Discussion -- 5.1 Experiment 1: Ranking of Super-Resolution Methods -- 5.2 Experiment 2: Impact of Super-Resolution on Aerial Scene Classification -- 6 Conclusion -- References -- Weeds Classification with Deep Learning: An Investigation Using CNN, Vision Transformers, Pyramid Vision Transformers, and Ensemble Strategy -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Datasets -- 3.2 Models -- 3.3 Ensemble -- 3.4 Evaluation -- 3.5 Training Configuration -- 3.6 Execution Environment -- 4 Results and Discussion -- 5 Conclusions -- References -- Leveraging Question Answering for Domain-Agnostic Information Extraction -- 1 Introduction -- 2 Related Work -- 3 Question Answering for Information Extraction -- 3.1 Models and Questions -- 3.2 Approach -- 3.3 Visual Explainability on Evaluation -- 4 Case Studies -- 4.1 Application to Toxicology Analysis -- 4.2 Application to Finance -- 5 Conclusion -- References -- Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves -- 1 Introduction -- 2 Dataset Collection -- 3 Proposed Approach -- 3.1 Image-to-Text Track -- 3.2 Localization Track -- 3.3 Selection Track -- 3.4 Report Generation -- 4 Results -- 5 Conclusions and Future Works. References -- A Self-Organizing Map Clustering Approach to Support Territorial Zoning -- 1 Introduction -- 2 Related Work -- 2.1 Zoning with Self-Organizing Maps -- 2.2 Clustering Ordinal Categorical Data -- 3 Material and Methods -- 3.1 The Alto Taquari Basin - MS/MT, Brazil -- 3.2 Clustering Categorical Ordinal Data -- 3.3 Clustering Assessing -- 4 Results and Discussion -- 5 Conclusions -- References -- Spatial-Temporal Graph Transformer for Surgical Skill Assessment in Simulation Sessions -- 1 Introduction -- 2 Proposed Approach -- 2.1 Spectral Graph Convolutional Networks -- 2.2 Transformer Encoder -- 2.3 Surgical Skill Classifier -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Results -- 4 Conclusion -- References -- Deep Learning in the Identification of Psoriatic Skin Lesions -- 1 Introduction -- 2 Background and Literature Review -- 3 Methodology -- 3.1 Understanding the Problem -- 3.2 Deep Learning -- 3.3 Dataset -- 3.4 Classification Architectures -- 3.5 Training -- 4 Results -- 4.1 CLAHE -- 4.2 Type of Input Image -- 4.3 Data Augmentation -- 5 Discussion -- 6 Mobile Application -- 7 Conclusion -- References -- WildFruiP: Estimating Fruit Physicochemical Parameters from Images Captured in the Wild -- 1 Introduction -- 2 Related Work -- 2.1 Detection Methods -- 2.2 Segmentation Methods -- 2.3 Methods for Estimating Fruit Ripeness in Images -- 3 Proposed Method -- 3.1 Fruit Detection and Segmentation -- 3.2 Image Alignment -- 3.3 Determination of Physicochemical Parameters -- 4 Dataset -- 5 Experiments -- 5.1 Implementation Details -- 5.2 Metrics -- 5.3 Performance of the Proposed Approach -- 5.4 Impact of Alignment Phase -- 5.5 Impact of Model Architecture -- 5.6 Hard Samples -- 6 Conclusion and Future Work Prospects -- References. Depression Detection Using Deep Learning and Natural Language Processing Techniques: A Comparative Study. |
Record Nr. | UNINA-9910766892403321 |
Vasconcelos Verónica
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
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Lo trovi qui: Univ. Federico II | ||
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