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Statistical Machine Learning for Human Behaviour Analysis
| Statistical Machine Learning for Human Behaviour Analysis |
| Autore | Moeslund Thomas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (300 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
3D convolutional neural networks
accuracy action recognition adaptive classifiers age classification attention allocation attention behavior biometric recognition blurring detection body movements boundary segmentation categorical data committee of classifiers concept drift context-aware framework convolutional neural network deep learning discrete stationary wavelet transform emotion recognition Empatica E4 ensemble methods face analysis face segmentation false negative rate fibromyalgia fingerprint image enhancement fingerprint quality foggy image frequency domain gait event gender classification gestures hand sign language head pose estimation hybrid entropy individual behavior estimation information entropy interpretable machine learning k-means clustering Kinect sensor Learning Using Concave and Convex Kernels multi-modal multi-objective evolutionary algorithms multimodal-based human identification neural networks noisy image object contour detection privacy privacy-aware profoundly deaf recurrent concepts restricted Boltzmann machine (RBM) rule-based classifiers saliency detection self-reported survey silhouettes difference single pixel single photon image acquisition singular point detection spatial domain spectrograms speech speech emotion recognition statistical-based time-frequency domain and crowd condition stock price direction prediction time-of-flight toe-off detection |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557288403321 |
Moeslund Thomas
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Virtual Reality in the Assessment, Understanding and Treatment of Mental Health Disorders
| Virtual Reality in the Assessment, Understanding and Treatment of Mental Health Disorders |
| Autore | Riva Giuseppe |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (316 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
adults
aging Alzheimer disease amputee patients anorexia nervosa anxiety disorders autism spectrum disorder bodily-self body anxiety body dissatisfaction body image distortion body image disturbances body movements body representation cognitive and physical rehabilitation cognitive assessment cognitive exposure cognitive rehabilitation computational models computerized assessment cross-validation decision tree dementia dental anxiety derealization digital biomarker distraction systems electroencephalogram embodied cognition embodiment emotion regulation enactment episodic memory executive functions exposure in virtual reality fear of gaining weight fMRI full body illusion Generalized Anxiety Disorder (GAD) hallucinations health hippocampus interpersonal multisensory stimulation machine learning memory rehabilitation mental health metacognition mild cognitive impairment MRI multiple errands test n/a navigation neuroimaging neurorehabilitation obesity Obsessive-compulsive disorders oldest old person pain pain perception personalized scenario presence psychosis real phobic images repetitive behaviors sense of agency sense of reality serious game spatial memory specific phobia standardized scenario stress systematic review telescoped effect treatment virtual environment virtual reality wellbeing intervention |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557760003321 |
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Riva Giuseppe
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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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