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.
Artificial Intelligence for Multimedia Signal Processing
| Artificial Intelligence for Multimedia Signal Processing |
| Autore | Kim Byung-Gyu |
| Pubbl/distr/stampa | Basel, : MDPI Books, 2022 |
| Descrizione fisica | 1 electronic resource (212 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
human-height estimation
depth video depth 3D conversion artificial intelligence convolutional neural networks deep neural network convolutional neural network environmental sound recognition feature combination multimodal joint representation content curation social networks different recommend tasks content based recommend systems scene/place classification semantic segmentation deep learning weighting matrix speech enhancement generative adversarial network relativistic GAN lightweight neural network single image super-resolution image enhancement image restoration residual dense networks visual sentiment analysis sentiment classification graph convolutional networks generative adversarial networks traffic surveillance image processing image de-raining fluency evaluation speech recognition data augmentation variational autoencoder speech conversion heartbeat classification convolutional neural network (CNN) canonical correlation analysis (CCA) Indian Sign Language (ISL) natural language processing avatar sign movement context-free grammar object detection logical story unit detection (LSU) object re-ID computer vision image processing single image artifacts reduction dense networks residual networks channel attention networks |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595077003321 |
Kim Byung-Gyu
|
||
| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Techniques and Applications of UAV-Based Photogrammetric 3D Mapping
| Techniques and Applications of UAV-Based Photogrammetric 3D Mapping |
| Autore | Jiang Wanshou |
| Pubbl/distr/stampa | Basel, : MDPI Books, 2022 |
| Descrizione fisica | 1 electronic resource (294 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
compound building reconstruction
LiDAR point clouds semantic decomposition structure from motion match pair cycle consistency inference repetitive structure very short baseline high-resolution remote sensing images building extraction multiscale features aggregate semantic information feature pyramid spatial eight-quadrant kernel convolution 3D point cloud semantic segmentation indoor scene wide-baseline stereo image deep learning convolutional neural network affine invariant feature image matching photogrammetric mesh model building façade 3D reconstruction least square fitting single image super-resolution lightweight image super-resolution U-shaped residual network dense shortcut effective feature distillation high-frequency loss power lines UAV inspection red-black propagation depth map fusion PatchMatch digital photogrammetry camera self-calibration Brown model polynomial model aerial triangulation GF-7 image building footprint building height multi-view point cloud multi-view reconstruction detail preserving depth estimation surface meshing texture mapping coplanar extraction deep convolutional neural network geometric topology homography matrix airborne LiDAR coal mine surface subsidence deformation detection digital subsidence model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910595072603321 |
|
Jiang Wanshou
|
||
| Basel, : MDPI Books, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||