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Advanced Computational Methods for Oncological Image Analysis
| Advanced Computational Methods for Oncological Image Analysis |
| Autore | Rundo Leonardo |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (262 p.) |
| Soggetto topico | Medicine and Nursing |
| Soggetto non controllato |
3D-CNN
bone scintigraphy brain MRI image brain tumor brain tumor segmentation BRATS dataset breast cancer breast cancer detection breast cancer diagnosis breast imaging breast mass classification clutter rejection computer-aided detection contrast source inversion dataset partition deep learning dimensionality reduction ensemble classification ensemble method false positives reduction feature selection image reconstruction imaging biomarkers immunotherapy incoherent imaging interferometric optical fibers k-means clustering Kolmogorov-Smirnov hypothesis test machine learning magnetic resonance imaging mammography Mask R-CNN mass detection mass segmentation medical imaging melanoma detection microwave imaging MRgFUS n/a performance metrics principal component analysis prostate cancer proton resonance frequency shift radiomics RBF neural networks referenceless thermometry region growing risk assessment segmentation self-attention semisupervised classification shallow machine learning skull stripping statistical inference survey temperature variations texture transfer learning tumor region U-Net unsupervised machine learning Wisconsin Breast Cancer Dataset |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557353503321 |
Rundo Leonardo
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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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Advances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming
| Advances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming |
| Autore | Qiao Yongliang |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (228 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
absorbing Markov chain
additive manufacturing animal behaviour animal farming animal science animal telemetry animal-centered design audio automated medical image processing body size cascaded model class-balanced focal loss commercial aviary computational ethology computer vision convolutional neural network cow cow behavior analysis cow identification CT scans dairy cow dairy welfare deep learning deep neural network design contributions EfficientDet equine behavior estimation extensive livestock false registrations forage management generative adversarial network group-housed pigs hierarchical clustering instance segmentation intermodality interaction jaw movement laying hens low-frequency tracking machine learning mask scoring R-CNN mastication modularity monitoring mutual information parturition prediction pig identification pig weight precision livestock farming precision livestock management prediction of calving time radar sensors radar signal processing sensorized wearable device signal classification smart collar soft-NMS time budgets tree-based classifier unsupervised machine learning wavelet analysis wearable sensor wearables design YOLACT++ |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576879803321 |
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Qiao Yongliang
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics / Felix Fritzen, David Ryckelynck
| Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics / Felix Fritzen, David Ryckelynck |
| Autore | Fritzen Felix |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (254 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
supervised machine learning
proper orthogonal decomposition (POD) PGD compression stabilization nonlinear reduced order model gappy POD symplectic model order reduction neural network snapshot proper orthogonal decomposition 3D reconstruction microstructure property linkage nonlinear material behaviour proper orthogonal decomposition reduced basis ECSW geometric nonlinearity POD model order reduction elasto-viscoplasticity sampling surrogate modeling model reduction enhanced POD archive modal analysis low-rank approximation computational homogenization artificial neural networks unsupervised machine learning large strain reduced-order model proper generalised decomposition (PGD) a priori enrichment elastoviscoplastic behavior error indicator computational homogenisation empirical cubature method nonlinear structural mechanics reduced integration domain model order reduction (MOR) structure preservation of symplecticity heterogeneous data reduced order modeling (ROM) parameter-dependent model data science Hencky strain dynamic extrapolation tensor-train decomposition hyper-reduction empirical cubature randomised SVD machine learning inverse problem plasticity proper symplectic decomposition (PSD) finite deformation Hamiltonian system DEIM GNAT |
| ISBN |
9783039214105
3039214101 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367759403321 |
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Fritzen Felix
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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