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Deep Learning in Medical Image Analysis
| Deep Learning in Medical Image Analysis |
| Autore | Zhang Yudong |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (458 p.) |
| Soggetto non controllato |
interpretable/explainable machine learning
image classification image processing machine learning models white box black box cancer prediction deep learning multimodal learning convolutional neural networks autism fMRI texture analysis melanoma glcm matrix machine learning classifiers explainability explainable AI XAI medical imaging diagnosis ARMD change detection unsupervised learning microwave breast imaging image reconstruction tumor detection digital pathology whole slide image processing multiple instance learning deep learning classification HER2 medical images transfer learning optimizers neo-adjuvant treatment tumour cellularity cancer breast cancer diagnostics imaging computation artificial intelligence 3D segmentation active surface discriminant analysis PET imaging medical image analysis brain tumor cervical cancer colon cancer lung cancer computer vision musculoskeletal images lung disease detection taxonomy convolutional neural network CycleGAN data augmentation dermoscopic images domain transfer macroscopic images skin lesion segmentation infection detection COVID-19 X-ray images bayesian inference shifted-scaled dirichlet distribution MCMC gibbs sampling object detection surgical tools open surgery egocentric camera computers in medicine segmentation MRI ECG signal detection portable monitoring devices 1D-convolutional neural network medical image segmentation domain adaptation meta-learning U-Net computed tomography (CT) magnetic resonance imaging (MRI) low-dose sparse-angle quantitative comparison |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557435103321 |
Zhang Yudong
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Innovative Learning Environments in STEM Higher Education [[electronic resource] ] : Opportunities, Challenges, and Looking Forward / / edited by Jungwoo Ryoo, Kurt Winkelmann
| Innovative Learning Environments in STEM Higher Education [[electronic resource] ] : Opportunities, Challenges, and Looking Forward / / edited by Jungwoo Ryoo, Kurt Winkelmann |
| Autore | Ryoo Jungwoo |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (XV, 137 p. 8 illus., 7 illus. in color.) |
| Disciplina | 519.5 |
| Collana | SpringerBriefs in Statistics |
| Soggetto topico |
Statistics
Machine learning Learning Instruction Knowledge representation (Information theory) Statistics for Social Sciences, Humanities, Law Machine Learning Statistics and Computing/Statistics Programs Learning & Instruction Knowledge based Systems Educació STEM Educació superior |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Statistics for Social Sciences, Humanities, Law
Machine Learning Statistics and Computing/Statistics Programs Learning & Instruction Knowledge based Systems Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistics and Computing Education Innovative Learning Environments ILEs Science, Technology, Engineering, and Math STEM virtual reality VR augmented reality mixed reality cross reality extended reality artificial intelligence AI adaptive learning personalized learning higher education multimodal learning mobile learning Open Access Social research & statistics Mathematical & statistical software Teaching skills & techniques Cognition & cognitive psychology Expert systems / knowledge-based systems |
| ISBN | 3-030-58948-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. X-FILEs Vision for personalized and Adaptive Learning -- 3. X-FILEs Vision for Multi-modal Learning Formats -- 4. X-FILEs Vision for Extended/Cross Reality (XR) -- 5. X-FILEs Vision for Artificial Intelligence (AI) and Machine Learning (ML) -- 6. Cross-Cutting Concerns -- 7. Epilogue. |
| Record Nr. | UNISA-996466564503316 |
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Ryoo Jungwoo
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| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Innovative Learning Environments in STEM Higher Education [[electronic resource] ] : Opportunities, Challenges, and Looking Forward / / edited by Jungwoo Ryoo, Kurt Winkelmann
| Innovative Learning Environments in STEM Higher Education [[electronic resource] ] : Opportunities, Challenges, and Looking Forward / / edited by Jungwoo Ryoo, Kurt Winkelmann |
| Autore | Ryoo Jungwoo |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Springer Nature, 2021 |
| Descrizione fisica | 1 online resource (XV, 137 p. 8 illus., 7 illus. in color.) |
| Disciplina | 519.5 |
| Collana | SpringerBriefs in Statistics |
| Soggetto topico |
Statistics
Machine learning Learning Instruction Knowledge representation (Information theory) Statistics for Social Sciences, Humanities, Law Machine Learning Statistics and Computing/Statistics Programs Learning & Instruction Knowledge based Systems Educació STEM Educació superior |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Statistics for Social Sciences, Humanities, Law
Machine Learning Statistics and Computing/Statistics Programs Learning & Instruction Knowledge based Systems Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistics and Computing Education Innovative Learning Environments ILEs Science, Technology, Engineering, and Math STEM virtual reality VR augmented reality mixed reality cross reality extended reality artificial intelligence AI adaptive learning personalized learning higher education multimodal learning mobile learning Open Access Social research & statistics Mathematical & statistical software Teaching skills & techniques Cognition & cognitive psychology Expert systems / knowledge-based systems |
| ISBN | 3-030-58948-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Introduction -- 2. X-FILEs Vision for personalized and Adaptive Learning -- 3. X-FILEs Vision for Multi-modal Learning Formats -- 4. X-FILEs Vision for Extended/Cross Reality (XR) -- 5. X-FILEs Vision for Artificial Intelligence (AI) and Machine Learning (ML) -- 6. Cross-Cutting Concerns -- 7. Epilogue. |
| Record Nr. | UNINA-9910473457603321 |
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Ryoo Jungwoo
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| Springer Nature, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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