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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 electronic resource (300 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
multi-objective evolutionary algorithms
rule-based classifiers interpretable machine learning categorical data hand sign language deep learning restricted Boltzmann machine (RBM) multi-modal profoundly deaf noisy image ensemble methods adaptive classifiers recurrent concepts concept drift stock price direction prediction toe-off detection gait event silhouettes difference convolutional neural network saliency detection foggy image spatial domain frequency domain object contour detection discrete stationary wavelet transform attention allocation attention behavior hybrid entropy information entropy single pixel single photon image acquisition time-of-flight action recognition fibromyalgia Learning Using Concave and Convex Kernels Empatica E4 self-reported survey speech emotion recognition 3D convolutional neural networks k-means clustering spectrograms context-aware framework accuracy false negative rate individual behavior estimation statistical-based time-frequency domain and crowd condition emotion recognition gestures body movements Kinect sensor neural networks face analysis face segmentation head pose estimation age classification gender classification singular point detection boundary segmentation blurring detection fingerprint image enhancement fingerprint quality speech committee of classifiers biometric recognition multimodal-based human identification privacy privacy-aware |
| 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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The Convergence of Human and Artificial Intelligence on Clinical Care - Part I
| The Convergence of Human and Artificial Intelligence on Clinical Care - Part I |
| Autore | Abedi Vida |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (188 p.) |
| Soggetto topico | Medicine |
| Soggetto non controllato |
machine learning-enabled decision support system
improving diagnosis accuracy Bayesian network bariatric surgery health-related quality of life comorbidity voice change larynx cancer machine learning deep learning voice pathology classification imputation electronic health records EHR laboratory measures medical informatics inflammatory bowel disease C. difficile infection osteoarthritis complex diseases healthcare artificial intelligence interpretable machine learning explainable machine learning septic shock clinical decision support system electronic health record cerebrovascular disorders stroke SARS-CoV-2 COVID-19 cluster analysis risk factors ischemic stroke outcome prediction recurrent stroke cardiac ultrasound echocardiography portable ultrasound aneurysm surgery temporary artery occlusion clipping time artificial neural network digital imaging monocytes promonocytes and monoblasts chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) for acute monoblastic leukemia and acute monocytic leukemia concordance between hematopathologists mechanical ventilation respiratory failure ADHD social media pharmacotherapy stimulants alpha-2-adrenergic agonists non-stimulants trust passive adherence human factors |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557617803321 |
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Abedi Vida
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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