Visual and Camera Sensors

• Autore: Park Kang Ryoung
• Pubblicazione: 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
• Persona (resp. second.): LeeSangyoun; KimEuntai; ParkKang Ryoung
• Sommario/riassunto: This book includes 13 papers published in Special Issue ("Visual and Camera Sensors") of the journal Sensors. The goal of this Special Issue was to invite high-quality, state-of-the-art research papers dealing with challenging issues in visual and camera sensors.
• Titolo autorizzato: Visual and Camera Sensors
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557360203321
• Lo trovi qui: Univ. Federico II