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Image Analysis and Processing - ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23-27, 2022, Proceedings, Part I / / Stan Sclaroff [and four others], editors
| Image Analysis and Processing - ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23-27, 2022, Proceedings, Part I / / Stan Sclaroff [and four others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] |
| Descrizione fisica | 1 online resource (814 pages) |
| Disciplina | 006.37 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Image analysis
Image processing |
| ISBN | 3-031-06427-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Contents - Part III -- Brave New Ideas -- A Lightweight Model for Satellite Pose Estimation -- 1 Introduction -- 2 Methodology and Data -- 2.1 Processing Pipeline -- 2.2 The Dataset -- 3 Experimental Results -- 4 Conclusions -- References -- Imitation Learning for Autonomous Vehicle Driving: How Does the Representation Matter? -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Benchmark -- 3.3 The Investigated CIL Method -- 3.4 Analysis of the Input Representation -- 3.5 Training Procedure -- 4 Experimental Results -- 5 Conclusions -- References -- LessonAble: Leveraging Deep Fakes in MOOC Content Creation -- 1 Introduction -- 2 Methodology -- 2.1 Voice Generation -- 2.2 Video Generation -- 2.3 Lip-syncing -- 3 Use Case -- 4 Conclusion -- References -- An Intelligent Scanning Vehicle for Waste Collection Monitoring -- 1 Introduction -- 2 Related Work -- 3 Intelligent Waste Recognition System -- 4 Hardware Design -- 5 Software Design -- 5.1 Data Preprocessing -- 5.2 Intelligent Waste Segmentation -- 5.3 Result Analysis and Communication -- 6 Results -- 7 Conclusion -- References -- Morphological Galaxies Classification According to Hubble-de Vaucouleurs Diagram Using CNNs -- 1 Introduction -- 2 Problem Statement -- 2.1 Galaxy Zoo Dataset -- 2.2 Data Augmentation -- 3 Method -- 3.1 Proposed Architecture -- 3.2 CNNs Based on Well-Known Backbones -- 4 Experimental Results -- 5 Conclusions -- References -- Biomedical and Assistive Technology -- Pulmonary-Restricted COVID-19 Informative Visual Screening Using Chest X-ray Images from Portable Devices -- 1 Introduction -- 2 Materials -- 3 Methodology -- 3.1 Region of Interest Extraction -- 3.2 COVID-19 Screening -- 4 Results and Discussion -- 4.1 Training Results -- 4.2 Test Results.
5 Conclusions -- References -- Comparison of Different Supervised and Self-supervised Learning Techniques in Skin Disease Classification -- 1 Introduction -- 2 Related Work -- 2.1 Self-supervised Learning -- 2.2 On ISIC 2019 Dataset -- 3 Method -- 3.1 Loss and Optimizer -- 3.2 Choosing CNN and Input Image Size -- 3.3 Data Augmentations -- 4 Experimental Results -- 4.1 Self-supervised Experiments -- 5 Conclusion and Future Work -- References -- Unsupervised Deformable Image Registration in a Landmark Scarcity Scenario: Choroid OCTA -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Network Architecture -- 2.3 Training Details -- 2.4 Baseline Methods -- 2.5 Evaluation Metric -- 3 Results and Discussion -- 3.1 Quantitative Evaluation -- 3.2 Qualitative Evaluation -- 4 Conclusions -- References -- Leveraging CycleGAN in Lung CT Sinogram-free Kernel Conversion -- 1 Introduction -- 2 Methodology -- 2.1 Pre-processing -- 2.2 Kernel Conversion -- 3 Experimental Setup -- 4 Results -- 5 Conclusion -- References -- Investigating One-Class Classifiers to Diagnose Alzheimer's Disease from Handwriting -- 1 Introduction -- 2 Related Works -- 3 One-class Classifiers -- 3.1 RNSA -- 3.2 Isolation Forest -- 3.3 One-class Support Vector Machine -- 4 Experimental Results -- 4.1 Dataset -- 4.2 Features Selection -- 4.3 Performance Evaluation -- 5 Discussion and Conclusions -- References -- Learning Unrolling-Based Neural Network for Magnetic Resonance Imaging Reconstruction -- 1 Introduction -- 2 Related Work -- 2.1 Deep Learning for MR Imaging -- 2.2 Unrolling-Based Deep Learning Approaches -- 3 Approach -- 3.1 Overall Architecture -- 3.2 Improved Swin Transformer Blocks of UTrans -- 4 Experiments -- 4.1 Datasets and Baseline Models -- 4.2 Implementation Details -- 4.3 Result and Evaluation -- 4.4 Ablation Analysis -- 5 Conclusion -- References. Machine Learning to Predict Cognitive Decline of Patients with Alzheimer's Disease Using EEG Markers: A Preliminary Study -- 1 Introduction -- 2 EEG Features -- 3 Cognitive Tests and Scales -- 4 Experimental Results -- 5 Conclusions -- References -- Improving AMD Diagnosis by the Simultaneous Identification of Associated Retinal Lesions -- 1 Introduction -- 2 Materials and Methods -- 2.1 Prediction Loss -- 2.2 Network Architecture -- 2.3 Data -- 2.4 Training Details -- 3 Results and Discussion -- 4 Conclusions -- References -- Eye Diseases Classification Using Deep Learning -- 1 Introduction -- 1.1 Motivation -- 1.2 Overview of the Study -- 2 Related Work -- 2.1 Diabetic Retinopathy -- 2.2 Glaucoma -- 2.3 Cataract -- 3 Datasets -- 4 Synergic Deep Learning -- 5 Segmentation -- 6 Experiments Results -- 6.1 Initial Approach -- 6.2 Individual Diseases Classification -- 6.3 Multiple Diseases Classification -- 6.4 Comparison to Standard DCNN Model -- 7 Discussion -- 8 Conclusions -- References -- A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images -- 1 Introduction -- 2 Datasets -- 3 Radiological Report -- 3.1 Architecture -- 3.2 Dealing with Uncertain Labels -- 4 COVID Diagnosis -- 5 Experiments -- 6 Conclusions -- References -- UniToChest: A Lung Image Dataset for Segmentation of Cancerous Nodules on CT Scans -- 1 Introduction -- 2 Background and Related Works -- 3 The UniToChest Dataset -- 4 Methodology -- 4.1 Data Preprocessing -- 4.2 Network Architecture -- 4.3 Training Procedure -- 5 Results and Discussion -- 5.1 Nodules Segmentation -- 5.2 Detection -- 6 Conclusion and Future Works -- References -- Optimized Fusion of CNNs to Diagnose Pulmonary Diseases on Chest X-Rays -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Pre-processing -- 3.2 Training of Single CNNs -- 3.3 Ensemble Optimization. 4 Results and Discussions -- 5 Conclusions -- References -- High/Low Quality Style Transfer for Mutual Conversion of OCT Images Using Contrastive Unpaired Translation Generative Adversarial Networks -- 1 Introduction -- 2 Methodology -- 3 Results and Discussion -- 4 Conclusions -- References -- Real-Time Respiration Monitoring of Neonates from Thermography Images Using Deep Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Experimental Setup and Dataset -- 2.2 Data Preprocessing -- 2.3 Detector Training and Validation -- 2.4 Respiration Extraction -- 2.5 Real-Time Feasibility on Embedded GPUs -- 3 Results and Discussion -- 3.1 Detector Accuracy -- 3.2 Respiration Extraction -- 3.3 Inference Performance -- 4 Conclusion and Outlook -- References -- Improving Colon Carcinoma Grading by Advanced CNN Models -- 1 Introduction -- 2 Methods and Data -- 2.1 Advanced Deep Network Architectures -- 2.2 The Datasets: CRC and Extended CRC -- 3 Experimental Results on the Extended CRC Dataset -- 3.1 Comparisons to Leading Approaches in the Literature -- 4 Conclusion -- References -- Multimedia -- Frame Adaptive Rate Control Scheme for Video Compressive Sensing -- 1 Introduction -- 2 Proposed Frame Adaptive Rate Control Scheme -- 2.1 Overall System -- 2.2 Triangle Quantization for QP Initialization -- 2.3 Frame Adaptive QP Adjustment and Block-Based QP Refinement -- 3 Results and Comparison -- 3.1 Quantization Performance Comparison -- 3.2 Rate Control Performance Comparison -- 4 Conclusion -- References -- Shot-Based Hybrid Fusion for Movie Genre Classification -- 1 Introduction -- 2 Shot-Based Hybrid Fusion Networks -- 2.1 Video-Net -- 2.2 Audio-Net -- 2.3 Multi-modal Feature Fusion and Decision Fusion -- 3 Experiments and Results -- 3.1 Dataset and Data Preprocessing -- 3.2 Models Variations for Evaluation. 3.3 Experiment Settings and Evaluation Metrics -- 3.4 Results and Discussion -- 4 Conclusion -- References -- Landmark-Guided Conditional GANs for Face Aging -- 1 Introduction -- 2 Related Work -- 3 The Proposed Methods -- 3.1 Network Architecture -- 3.2 Objective Functions -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Qualitative Comparison -- 4.3 Quantitative Comparison -- 5 Conclusion -- References -- Introducing AV1 Codec-Level Video Steganography -- 1 Introduction -- 2 Related Works -- 3 Steganography on AV1 Codec-level -- 4 Experiments and Evaluation -- 4.1 Solution Capabilities -- 4.2 Visual Quality Preservation -- 4.3 Discussion -- 5 Conclusions and Future Works -- References -- Deep Learning -- Efficient Transfer Learning for Visual Tasks via Continuous Optimization of Prompts -- 1 Introduction -- 2 Methods -- 2.1 Pre-training -- 2.2 Fine-Tuning -- 2.3 Datasets -- 2.4 Training Procedure -- 3 Results -- 3.1 Classification -- 3.2 Few-Shot Classification -- 4 Discussion -- 4.1 Applications -- 4.2 Hyperparameters for VPT -- 4.3 Conclusion -- References -- Continual Learning with Neuron Activation Importance -- 1 Introduction -- 2 Proposed Method -- 2.1 Neuron Importance by Average Neuron Activation -- 2.2 Weight Re-initialization for Better Plasticity -- 3 Experimental Evaluations -- 3.1 MNIST -- 3.2 Split CIFAR10 -- 3.3 Split CIFAR10-100 -- 3.4 Split Tiny ImageNet -- 4 Conclusion -- References -- AD-CGAN: Contrastive Generative Adversarial Network for Anomaly Detection -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Proposed Approach -- 4.1 Contrastive GAN -- 4.2 Autoencoder -- 4.3 Latent Space Discriminator -- 4.4 Normality Score -- 5 Experimental Results -- 5.1 Datasets -- 5.2 Baseline Methods -- 5.3 Results -- 5.4 Ablation Study -- 6 Conclusion and Future Work -- References. Analyzing EEG Data with Machine and Deep Learning: A Benchmark. |
| Record Nr. | UNISA-996475771903316 |
| Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Image analysis and processing -- ICIAP 2022 : 21st international conference, Lecce, Italy, May 23-27, 2022, proceedings : part III / / edited by Stan Sclaroff [and four others]
| Image analysis and processing -- ICIAP 2022 : 21st international conference, Lecce, Italy, May 23-27, 2022, proceedings : part III / / edited by Stan Sclaroff [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (507 pages) |
| Disciplina | 006.6 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image analysis
Image processing - Digital techniques |
| ISBN | 3-031-06433-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996475771503316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Image analysis and processing -- ICIAP 2022 . Part II : 21st international conference, Lecce, Italy, May 23-27, 2022 : proceedings / / Stan Sclaroff [and four others]
| Image analysis and processing -- ICIAP 2022 . Part II : 21st international conference, Lecce, Italy, May 23-27, 2022 : proceedings / / Stan Sclaroff [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2022] |
| Descrizione fisica | 1 online resource (786 pages) |
| Disciplina | 621.367 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image analysis
Image processing - Digital techniques |
| ISBN | 3-031-06430-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996475770803316 |
| Cham, Switzerland : , : Springer International Publishing, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part II / / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari
| Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part II / / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (786 pages) |
| Disciplina | 621.367 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer engineering Computer networks Machine learning Pattern recognition systems Application software Computer Vision Computer Engineering and Networks Machine Learning Computer Communication Networks Automated Pattern Recognition Computer and Information Systems Applications |
| ISBN | 3-031-06430-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | M ultiview Geometry and 3D Computer Vision -- Digital Forensics and Biometrics -- Image Analysis, Detection and Recognition. |
| Record Nr. | UNINA-9910569193503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part I / / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari
| Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part I / / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (814 pages) |
| Disciplina | 006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Application software Education - Data processing Social sciences - Data processing Machine learning Pattern recognition systems Computer Vision Computer and Information Systems Applications Computers and Education Computer Application in Social and Behavioral Sciences Machine Learning Automated Pattern Recognition |
| ISBN | 3-031-06427-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Brave New Ideas -- Biomedical and Assistive Technology -- Multimedia -- Deep Learning -- Image Processing for Cultural Heritage -- Robot Vision. |
| Record Nr. | UNINA-9910568298603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part III / / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari
| Image Analysis and Processing – ICIAP 2022 : 21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part III / / edited by Stan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (507 pages) |
| Disciplina |
006.6
621.367 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer engineering Computer networks Machine learning Education - Data processing Pattern recognition systems Computer Vision Computer Engineering and Networks Machine Learning Computers and Education Automated Pattern Recognition |
| ISBN | 3-031-06433-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pattern Recognition and Machine Learning -- Video Analysis & Understanding -- Special Session. |
| Record Nr. | UNINA-9910568290503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Pattern Recognition. ICPR International Workshops and Challenges [[electronic resource] ] : Virtual Event, January 10–15, 2021, Proceedings, Part VI / / edited by Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani
| Pattern Recognition. ICPR International Workshops and Challenges [[electronic resource] ] : Virtual Event, January 10–15, 2021, Proceedings, Part VI / / edited by Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XX, 821 p. 323 illus., 277 illus. in color.) |
| Disciplina | 006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Application software Artificial intelligence Computers Computer Vision Computer and Information Systems Applications Artificial Intelligence Computing Milieux |
| ISBN | 3-030-68780-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464428603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Pattern Recognition. ICPR International Workshops and Challenges : Virtual Event, January 10–15, 2021, Proceedings, Part VI / / edited by Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani
| Pattern Recognition. ICPR International Workshops and Challenges : Virtual Event, January 10–15, 2021, Proceedings, Part VI / / edited by Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XX, 821 p. 323 illus., 277 illus. in color.) |
| Disciplina |
006.37
006.4 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Application software Artificial intelligence Computers Computer Vision Computer and Information Systems Applications Artificial Intelligence Computing Milieux |
| ISBN | 3-030-68780-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483556603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Visual Saliency: From Pixel-Level to Object-Level Analysis / / by Jianming Zhang, Filip Malmberg, Stan Sclaroff
| Visual Saliency: From Pixel-Level to Object-Level Analysis / / by Jianming Zhang, Filip Malmberg, Stan Sclaroff |
| Autore | Zhang Jianming (Research scientist) |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (138 pages) |
| Disciplina |
621.367
006.42 |
| Soggetto topico |
Optical data processing
Signal processing Image processing Speech processing systems Computer science - Mathematics Image Processing and Computer Vision Signal, Image and Speech Processing Mathematics of Computing |
| ISBN | 3-030-04831-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Overview -- 2 Boolean Map Saliency: A Surprisingly Simple Method -- 3 A Distance Transform Perspective -- 4 Efficient Distance Transform for Salient Region Detection -- 5 Salient Object Subitizing -- 6 Unconstrained Salient Object Detection -- 7 Conclusion and Future Work. |
| Record Nr. | UNINA-9910337571303321 |
Zhang Jianming (Research scientist)
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||