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.
Innovations in Photogrammetry and Remote Sensing : Modern Sensors, New Processing Strategies and Frontiers in Applications
| Innovations in Photogrammetry and Remote Sensing : Modern Sensors, New Processing Strategies and Frontiers in Applications |
| Autore | Pirotti Francesco |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (216 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
3D reconstruction
artificial neural network Beirut camera calibration change detection computer vision Copernicus damage proxy map deep learning dense image matching dense image matching (DIM) dense point cloud digital elevation model dome effect enhancement explosion geometric error GNSS-assisted block orientation high-precision calibration image histogram image processing InSAR isolated objects Lebanon mesh model modeling Monte Carlo simulation multiple view stereo (MVS) n/a natural disasters noise estimation optical flow estimation optical remote sensing image photogrammetry point cloud point clouds preprocessing radiometric calibration roughness sample optimization Sentinel-1 Sentinel-2 soil moisture content Structure from Motion (SfM) surface reconstruction synthetic aperture radar threshold selection UAV VHR tri-stereo satellite imagery visibility constraints volumetric methods |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Innovations in Photogrammetry and Remote Sensing |
| Record Nr. | UNINA-9910576883503321 |
Pirotti Francesco
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Visual and Camera Sensors
| Visual and Camera Sensors |
| Autore | Park Kang Ryoung |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (274 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
3D point clouds
accuracy analysis artificial intelligence automatic online calibration autonomous landing BIM blur image restoration camera calibration camera networks classification close range photogrammetry CNN computer vision computer-aided diagnosis convolutional auto-encoders convolutional filter convolutional neural network covariance DeblurGAN deep-learning-based motion deblurring and marker detection distortion partition DLT DoF-dependent drone ensemble learning facial expression recognition system flying object detection Hough-space image processing in vivo endoscopy lens distortion local image patch low-cost device machine learning multi-scale featured local binary pattern multi-sensor fusion multimodal human recognition network slimming OCD4M open-pit mine slope monitoring optimum deployment pathological site classification plank recognition PnP point pair feature portable mobile mapping system pruning model robotic grasping robustness self-assembly device semi-direct SLAM side-rear-view monitoring system three-dimensional reconstruction uncertainty unmanned aerial vehicle unsharp masking vision measurement visual-inertial VSLAM-photogrammetric algorithm weighted DLT |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557360203321 |
|
Park Kang Ryoung
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||