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.
Advances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming
| Advances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming |
| Autore | Qiao Yongliang |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (228 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
absorbing Markov chain
additive manufacturing animal behaviour animal farming animal science animal telemetry animal-centered design audio automated medical image processing body size cascaded model class-balanced focal loss commercial aviary computational ethology computer vision convolutional neural network cow cow behavior analysis cow identification CT scans dairy cow dairy welfare deep learning deep neural network design contributions EfficientDet equine behavior estimation extensive livestock false registrations forage management generative adversarial network group-housed pigs hierarchical clustering instance segmentation intermodality interaction jaw movement laying hens low-frequency tracking machine learning mask scoring R-CNN mastication modularity monitoring mutual information parturition prediction pig identification pig weight precision livestock farming precision livestock management prediction of calving time radar sensors radar signal processing sensorized wearable device signal classification smart collar soft-NMS time budgets tree-based classifier unsupervised machine learning wavelet analysis wearable sensor wearables design YOLACT++ |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576879803321 |
Qiao Yongliang
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Sensors for Vital Signs Monitoring
| Sensors for Vital Signs Monitoring |
| Autore | Yang Jong-Ryul |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (141 p.) |
| Soggetto topico |
Energy industries & utilities
Technology: general issues |
| Soggetto non controllato |
3D+t modeling
4D CT absolute distance measurement cage deformation cardiopulmonary resuscitation (CPR) carotid blood flow (CBF) cerebral circulation compensatory reserve cone-beam computed tomography continuous-wave radar coronary artery cross-correlation CW radar decomposition level denoising doppler cardiogram electroencephalogram (EEG) envelope detection frequency discrimination frequency-shift keying radar heartbeat accuracy improvement heartbeat detection hemodynamic data low-contrast object medical monitoring modulation transfer function mother wavelet function noise power spectrum non-rigid registration optimal filter passenger detection physiology radar feature vector radar machine learning radar signal processing signal decomposition signal-to-noise-ratio ultra-high resolution vital signs vital-signs monitoring wavelet transform wearable sensors |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557554603321 |
|
Yang Jong-Ryul
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||