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Artificial Intelligence for Multimedia Signal Processing
| Artificial Intelligence for Multimedia Signal Processing |
| Autore | Kim Byung-Gyu |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (212 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology History of engineering and technology |
| Soggetto non controllato |
human-height estimation
depth video depth 3D conversion artificial intelligence convolutional neural networks deep neural network convolutional neural network environmental sound recognition feature combination multimodal joint representation content curation social networks different recommend tasks content based recommend systems scene/place classification semantic segmentation deep learning weighting matrix speech enhancement generative adversarial network relativistic GAN lightweight neural network single image super-resolution image enhancement image restoration residual dense networks visual sentiment analysis sentiment classification graph convolutional networks generative adversarial networks traffic surveillance image processing image de-raining fluency evaluation speech recognition data augmentation variational autoencoder speech conversion heartbeat classification convolutional neural network (CNN) canonical correlation analysis (CCA) Indian Sign Language (ISL) natural language processing avatar sign movement context-free grammar object detection logical story unit detection (LSU) object re-ID computer vision image processing single image artifacts reduction dense networks residual networks channel attention networks |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595077003321 |
Kim Byung-Gyu
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence in Medical Image Processing and Segmentation
| Artificial Intelligence in Medical Image Processing and Segmentation |
| Autore | Zaffino Paolo |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2023 |
| Descrizione fisica | 1 online resource (348 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues History of engineering and technology |
| Soggetto non controllato |
2D ultrasound image
2D/3D registration 3D virtual reconstruction ALO artificial hummingbird algorithm artificial intelligence artificial neural network (ANN) attention mechanism auto-segmentation automatic volume measurement breast cancer breast density CAD canonical correlation analysis (CCA) carbon ion radiotherapy CBCT cervical cancer cervical net children CNN comparison computer vision applications convolutional neural network Convolutional Neural Networks Cranio-Maxillofacial surgery CT DarkNet-19 deep learning deep learning structures DICOM directional total variation disease discrimination accuracy dual-energy CT edge computing ensemble learning feature fusion feature selection fundus image GAN Grad-CAM hematoxylin eosin histopathological histopathology histopathology images image enhancement image inpainting image normalization image preprocessing image registration image segmentation image-guided radiotherapy in-house instance segmentation k-nearest neighbour (KNN) lesion segmentation limited-angular range loss function magnetic resonance imaging mandible mask-transformer-based networks medical image analysis medical imaging mitotic nuclei classification MobileNet mp-MRI MRI MRI guidance MRI-only multi-contrast MRI NasNet neuroimaging nuclei detection nuclei segmentation OCT orthogonal X-ray osteoarthritis ovarian tumor PA panoptic segmentation panoramic radiographs pap smear particle therapy patch size PCA PCNSL performance comparisons prostate cancer prostate segmentation pyramidal network radiomics random forest (RF) rare neurodevelopmental disorder rare tumor ResNet-101 safranin O fast green scale-adaptive segmentation semantic segmentation shuffle net ShuffleNet software support vector machine support vector machine (SVM) synthetic CT teeth segmentation textural tooth disease recognition tuberous sclerosis complex two-step method U-Net ultrasound bladder scanner urinary disease |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743276403321 |
| Zaffino Paolo | ||
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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