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Machine Learning in Sensors and Imaging
| Machine Learning in Sensors and Imaging |
| Autore | Nam Hyoungsik |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (302 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
star image
image denoising reinforcement learning maximum likelihood estimation mixed Poisson–Gaussian likelihood machine learning-based classification non-uniform foundation stochastic analysis vehicle–pavement–foundation interaction forest growing stem volume coniferous plantations variable selection texture feature random forest red-edge band on-shelf availability semi-supervised learning deep learning image classification machine learning explainable artificial intelligence wildfire risk assessment Naïve bayes transmission-line corridors image encryption compressive sensing plaintext related chaotic system convolutional neural network color prior model object detection piston error detection segmented telescope BP artificial neural network modulation transfer function computer vision intelligent vehicles extrinsic camera calibration structure from motion convex optimization temperature estimation BLDC electric machine protection touchscreen capacitive display SNR stylus laser cutting quality monitoring artificial neural network burr formation cut interruption fiber laser semi-supervised fuzzy noisy real-world plankton marine activity recognition wearable sensors imbalanced activities sampling methods path planning Q-learning neural network YOLO algorithm robot arm target reaching obstacle avoidance |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566484703321 |
Nam Hyoungsik
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Multi-Sensory Interaction for Blind and Visually Impaired People
| Multi-Sensory Interaction for Blind and Visually Impaired People |
| Autore | Cho Jun Dong |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (300 p.) |
| Soggetto topico |
The arts
Painting & paintings |
| Soggetto non controllato |
visually impaired people
accessibility art appreciation color temperature-depth coding thermal interaction user experience visually impaired color sound coding accessibility technology multimodal interaction auditory interface touch interface vision impairment visual impairment aesthetics multi-sensory museum exhibits color identification tactile perception cross modular association universal design people with visual impairment assistive technology auralization image accessibility touchscreen nonvisual feedback blind systematic review music recommendation system multimedia data processing weakly supervised learning soundscape music media art exhibition environments multi-sensory interaction multi-sensory interface scent interface |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557621203321 |
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Cho Jun Dong
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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