Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
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 electronic resource (262 p.) |
| Soggetto topico | Medicine |
| Soggetto non controllato |
melanoma detection
deep learning transfer learning ensemble classification 3D-CNN immunotherapy radiomics self-attention breast imaging microwave imaging image reconstruction segmentation unsupervised machine learning k-means clustering Kolmogorov-Smirnov hypothesis test statistical inference performance metrics contrast source inversion brain tumor segmentation magnetic resonance imaging survey brain MRI image tumor region skull stripping region growing U-Net BRATS dataset incoherent imaging clutter rejection breast cancer detection MRgFUS proton resonance frequency shift temperature variations referenceless thermometry RBF neural networks interferometric optical fibers breast cancer risk assessment machine learning texture mammography medical imaging imaging biomarkers bone scintigraphy prostate cancer semisupervised classification false positives reduction computer-aided detection breast mass mass detection mass segmentation Mask R-CNN dataset partition brain tumor classification shallow machine learning breast cancer diagnosis Wisconsin Breast Cancer Dataset feature selection dimensionality reduction principal component analysis ensemble method |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557353503321 |
Rundo Leonardo
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Automated Driving Systems
| Advances in Automated Driving Systems |
| Autore | Eichberger Arno |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (294 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
automated driving
scenario-based testing software framework traffic signs ADAS traffic sign recognition system cooperative perception ITS digital twin sensor fusion edge cloud autonomous drifting model predictive control (MPC) successive linearization adaptive control vehicle motion control varying road surfaces vehicle dynamics Mask R-CNN transfer learning inverse gamma correction illumination instance segmentation pedestrian custom dataset deep learning wheel loaders throttle prediction state prediction automation safety validation automated driving systems decomposition modular safety approval modular testing fault tree analysis adaptive cruise control informed machine learning physics-guided reinforcement learning safety autonomous vehicles autonomous conflict management UTM UAV UGV U-Space framework development lane detection simulation and modelling multi-layer perceptron convolutional neural network driver drowsiness ECG signal heart rate variability wavelet scalogram automated driving (AD) driving simulator expression of trust acceptance simulator case study NASA TLX advanced driver assistant systems (ADAS) system usability scale driving school virtual validation ground truth reference measurement calibration method simulation traffic evaluation simulation and modeling connected and automated vehicle driver assistance system virtual test and validation radar sensor physical perception model virtual sensor model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910580214003321 |
|
Eichberger Arno
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||