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 Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments
| Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| Autore | Woźniak Marcin |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (454 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
Traffic sign detection and tracking (TSDR)
advanced driver assistance system (ADAS) computer vision 3D convolutional neural networks machine learning CT brain brain hemorrhage visual inspection one-class classifier grow-when-required neural network evolving connectionist systems automatic design bio-inspired techniques artificial bee colony image analysis feature extraction ship classification marine systems citrus pests and diseases identification convolutional neural network parameter efficiency vehicle detection YOLOv2 focal loss anchor box multi-scale deep learning neural network generative adversarial network synthetic images tool wear monitoring superalloy tool image recognition object detection UAV imagery vehicular traffic flow detection vehicular traffic flow classification vehicular traffic congestion video classification benchmark semantic segmentation atrous convolution spatial pooling ship radiated noise underwater acoustics surface electromyography (sEMG) convolution neural networks (CNNs) hand gesture recognition fabric defect mixed kernels cross-scale cascaded center-ness deformable localization continuous casting surface defects 3D imaging defect detection object detector object tracking activity measure Yolo deep sort Hungarian algorithm optical flows spatiotemporal interest points sports scene CT images convolutional neural networks hepatic cancer visual question answering three-dimensional (3D) vision reinforcement learning human-robot interaction few shot learning SVM CNN cascade classifier video surveillance RFI artefacts InSAR image processing pixel convolution thresholding nearest neighbor filtering data acquisition augmented reality pose estimation industrial environments information retriever sensor multi-hop reasoning evidence chains complex search request high-speed trains hunting non-stationary feature fusion multi-sensor fusion unmanned aerial vehicles drone detection UAV detection visual detection |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557360703321 |
Woźniak Marcin
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Deep Learning-Based Action Recognition
| Deep Learning-Based Action Recognition |
| Autore | Lee Hyo Jong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (240 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
human action recognition
graph convolution high-order feature spatio-temporal feature feature fusion dynamic gesture recognition multi-modalities network class regularization 3D-CNN spatiotemporal activations class-specific features Dynamic Hand Gesture Recognition human-computer interaction hand shape features pose estimation stacked hourglass network deep learning convolutional receptive field hand gesture recognition human-machine interface artificial intelligence feedforward neural networks spatio-temporal image formation human activity recognition fusion strategies transfer learning activity recognition data augmentation multi-person pose estimation partitioned centerpose network partition pose representation continuous hand gesture recognition gesture spotting gesture classification multi-modal features 3D skeletal CNN spatiotemporal feature embedded system real-time action recognition Long Short-Term Memory spatio-temporal differential |
| ISBN | 3-0365-5200-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619465803321 |
|
Lee Hyo Jong
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||