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Artificial Intelligence in Medical Image Processing and Segmentation
| Artificial Intelligence in Medical Image Processing and Segmentation |
| 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 |
| 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 |
| MDPI - Multidisciplinary Digital Publishing Institute, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Learning Applications with Practical Measured Results in Electronics Industries
| Deep Learning Applications with Practical Measured Results in Electronics Industries |
| Autore | Kung Hsu-Yang |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (272 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
A*
background model binary classification CNN compressed sensing computational intelligence content reconstruction convolutional network data fusion data partition deep learning digital shearography discrete wavelet transform dot grid target eye-tracking device faster region-based CNN forecasting foreign object GA gated recurrent unit generative adversarial network geometric errors geometric errors correction GSA-BP human computer interaction humidity sensor hyperspectral image classification image compression image inpainting image restoration imaging confocal microscope Imaging Confocal Microscope information measure instance segmentation intelligent surveillance intelligent tire manufacturing K-means clustering kinematic modelling lateral stage errors Least Squares method long short-term memory machine learning MCM uncertainty evaluation multiple constraints multiple linear regression multivariate temporal convolutional network multivariate time series forecasting neighborhood noise reduction network layer contribution neural audio caption neural networks neuro-fuzzy systems nonlinear optimization offshore wind optimization techniques oral evaluation recommender system reinforcement learning residual networks rigid body kinematics saliency information smart grid supervised learning tire bubble defects tire quality assessment trajectory planning transfer learning UAV underground mines unmanned aerial vehicle unsupervised learning update mechanism update occasion visual tracking |
| ISBN | 3-03928-864-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404080403321 |
Kung Hsu-Yang
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) / John Ball, Bo Tang
| Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) / John Ball, Bo Tang |
| Autore | Ball John |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (344 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
FPGA
recurrence plot (RP) residual learning neural networks driver monitoring navigation depthwise separable convolution optimization dynamic path-planning algorithms object tracking sub-region cooperative systems convolutional neural networks DSRC VANET joystick road scene convolutional neural network (CNN) multi-sensor p-norm occlusion crash injury severity prediction deep leaning squeeze-and-excitation electric vehicles perception in challenging conditions T-S fuzzy neural network total vehicle mass of the front vehicle electrocardiogram (ECG) communications generative adversarial nets camera adaptive classifier updating Vehicle-to-X communications convolutional neural network predictive Geobroadcast infinity norm urban object detector machine learning automated-manual transition red light-running behaviors photoplethysmogram (PPG) panoramic image dataset parallel architectures visual tracking autopilot ADAS kinematic control GPU road lane detection obstacle detection and classification Gabor convolution kernel autonomous vehicle Intelligent Transport Systems driving decision-making model Gaussian kernel autonomous vehicles enhanced learning ethical and legal factors kernel based MIL algorithm image inpainting fusion terrestrial vehicle driverless drowsiness detection map generation object detection interface machine vision driving assistance blind spot detection deep learning relative speed autonomous driving assistance system discriminative correlation filter bank recurrent neural network emergency decisions LiDAR real-time object detection vehicle dynamics path planning actuation systems maneuver algorithm autonomous driving smart band the emergency situations two-wheeled support vector machine model global region biological vision automated driving |
| ISBN |
9783039213764
3039213768 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367757403321 |
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Ball John
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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