Visual Sensors
| 1. Verfasser: |
Reinoso Garcia, Oscar
, [VerfasserIn]
Payá, Luis , [VerfasserIn] |
|---|---|
| Umfang/Format: |
1 online resource (738 pages). |
| Schlagworte: | |
| Online Zugang: |
DOAB: download the publication DOAB: description of the publication |
| LEADER | 07106namaa2202293ui 4500 | ||
|---|---|---|---|
| 001 | 003028476 | ||
| 005 | 20221228154512.0 | ||
| 003 | DE-2553 | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20210212s2020 xx |||||o ||| 0|eng d | ||
| 020 | |a books978-3-03928-339-2 | ||
| 020 | |a 9783039283385 | ||
| 020 | |a 9783039283392 | ||
| 040 | |a oapen |c oapen |b eng |d DE-2553 |e rda | ||
| 024 | 7 | |a 10.3390/books978-3-03928-339-2 |c doi | |
| 041 | 0 | |a eng | |
| 042 | |a dc | ||
| 100 | 1 | |a Reinoso Garcia, Oscar |e author | |
| 264 | |b MDPI - Multidisciplinary Digital Publishing Institute, |c 2020. | ||
| 700 | 1 | |a Payá, Luis |e author | |
| 245 | 1 | 0 | |a Visual Sensors |
| 300 | |a 1 online resource (738 pages). | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a recognition algorithm | ||
| 653 | |a n/a | ||
| 653 | |a 3D ConvNets | ||
| 653 | |a consistent line clustering | ||
| 653 | |a skeletal data | ||
| 653 | |a fused point and line feature matching | ||
| 653 | |a soft decision tree | ||
| 653 | |a texture retrieval | ||
| 653 | |a vision system | ||
| 653 | |a laser sensor | ||
| 653 | |a neural network | ||
| 653 | |a iris segmentation | ||
| 653 | |a correlation filters | ||
| 653 | |a embedded systems | ||
| 653 | |a underwater imaging | ||
| 653 | |a stereo vision | ||
| 653 | |a seam-line | ||
| 653 | |a image processing | ||
| 653 | |a quality control | ||
| 653 | |a dynamic programming | ||
| 653 | |a visual information fusion | ||
| 653 | |a semantic segmentation | ||
| 653 | |a parallel line | ||
| 653 | |a textile retrieval | ||
| 653 | |a structure extraction | ||
| 653 | |a line scan camera | ||
| 653 | |a orientation relevance | ||
| 653 | |a measurement error | ||
| 653 | |a rotation-angle | ||
| 653 | |a star image prediction | ||
| 653 | |a convolutional neural network (CNN) | ||
| 653 | |a tightly-coupled VIO | ||
| 653 | |a visual sensors | ||
| 653 | |a stereo | ||
| 653 | |a parking assist system | ||
| 653 | |a visual detection | ||
| 653 | |a omnidirectional imaging | ||
| 653 | |a RGB-D SLAM | ||
| 653 | |a narrow butt joint | ||
| 653 | |a appearance-temporal features | ||
| 653 | |a vision-guided robotic grasping | ||
| 653 | |a scale invariance | ||
| 653 | |a support vector machine (SVM) | ||
| 653 | |a straight wing aircraft | ||
| 653 | |a statistical information of gray-levels differences | ||
| 653 | |a Local Binary Patterns | ||
| 653 | |a robotics | ||
| 653 | |a mobile robots | ||
| 653 | |a textile localization | ||
| 653 | |a indoor environment | ||
| 653 | |a CLOSIB | ||
| 653 | |a geometric moments | ||
| 653 | |a perceptually uniform histogram | ||
| 653 | |a single-shot 3D shape measurement | ||
| 653 | |a salient region detection | ||
| 653 | |a person re-identification | ||
| 653 | |a calibration | ||
| 653 | |a stereo camera | ||
| 653 | |a simplified initialization strategy | ||
| 653 | |a LSTM | ||
| 653 | |a SLAM | ||
| 653 | |a image mosaic | ||
| 653 | |a convolutional neural network | ||
| 653 | |a lane marking detection | ||
| 653 | |a finger alphabet | ||
| 653 | |a robot manipulation | ||
| 653 | |a patrol robot | ||
| 653 | |a inverse compositional Gauss-Newton algorithm | ||
| 653 | |a checkerboard | ||
| 653 | |a action localization | ||
| 653 | |a hybrid histogram descriptor | ||
| 653 | |a pivotal frames | ||
| 653 | |a lane marking reconstruction | ||
| 653 | |a warp function | ||
| 653 | |a visual localization | ||
| 653 | |a RGB-D | ||
| 653 | |a automatic calibration | ||
| 653 | |a Siamese network | ||
| 653 | |a object recognition | ||
| 653 | |a human visual system | ||
| 653 | |a LRF | ||
| 653 | |a Gray code | ||
| 653 | |a visual tracking | ||
| 653 | |a motion-aware | ||
| 653 | |a visual odometry | ||
| 653 | |a adaptive update strategy | ||
| 653 | |a Manhattan frame estimation | ||
| 653 | |a vibration | ||
| 653 | |a confidence response map | ||
| 653 | |a lane marking | ||
| 653 | |a 3D reconstruction | ||
| 653 | |a indoor visual SLAM | ||
| 653 | |a pose estimation | ||
| 653 | |a global feature descriptor | ||
| 653 | |a sweet pepper | ||
| 653 | |a texture classification | ||
| 653 | |a ego-motion estimation | ||
| 653 | |a pose estimates | ||
| 653 | |a planes intersection | ||
| 653 | |a adaptive model | ||
| 653 | |a support vector machines | ||
| 653 | |a motif co-occurrence histogram | ||
| 653 | |a handshape recognition | ||
| 653 | |a non-rigid reconstruction | ||
| 653 | |a camera calibration | ||
| 653 | |a map representation | ||
| 653 | |a optical flow | ||
| 653 | |a robotic welding | ||
| 653 | |a FOV | ||
| 653 | |a background dictionary | ||
| 653 | |a appearance based model | ||
| 653 | |a Visual Sensors | ||
| 653 | |a spatial transformation | ||
| 653 | |a star sensor | ||
| 653 | |a image retrieval | ||
| 653 | |a depth vision | ||
| 653 | |a iterative closest point | ||
| 653 | |a automated design | ||
| 653 | |a semantic mapping | ||
| 653 | |a regression based model | ||
| 653 | |a seam tracking | ||
| 653 | |a image binarization | ||
| 653 | |a GTAW | ||
| 653 | |a boosted decision tree | ||
| 653 | |a pedestrian detection | ||
| 653 | |a presentation attack detection | ||
| 653 | |a visible light and near-infrared light camera sensors | ||
| 653 | |a large field of view | ||
| 653 | |a fringe projection profilometry | ||
| 653 | |a sensors combination | ||
| 653 | |a catadioptric sensor | ||
| 653 | |a RGB-D sensor | ||
| 653 | |a texture description | ||
| 653 | |a UAV image | ||
| 653 | |a motion estimation | ||
| 653 | |a extrinsic calibration | ||
| 653 | |a visual sensor | ||
| 653 | |a advanced driver assistance system (ADAS) | ||
| 653 | |a content-based image retrieval | ||
| 653 | |a action segmentation | ||
| 653 | |a stereo-vision | ||
| 653 | |a visual mapping | ||
| 653 | |a around view monitor (AVM) system | ||
| 653 | |a illumination | ||
| 653 | |a speed measurement | ||
| 653 | |a Richardson-Lucy algorithm | ||
| 653 | |a digital image correlation | ||
| 653 | |a point cloud | ||
| 653 | |a receptive field correspondence | ||
| 653 | |a human visual attention | ||
| 653 | |a camera pose | ||
| 653 | |a sign language | ||
| 653 | |a symmetry axis | ||
| 653 | |a end-to-end architecture | ||
| 653 | |a local parallel cross pattern | ||
| 653 | |a iris recognition | ||
| 653 | |a depth image registration | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/2141 |7 0 |z DOAB: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/62289 |7 0 |z DOAB: description of the publication |
| 590 | |a Online publication | ||
| 590 | |a ebookoa1222 | ||
| 590 | |a doab | ||
| 942 | |2 z |c EB | ||
| 999 | |c 3028476 |d 1432231 | ||
| 952 | |0 0 |1 0 |2 z |4 0 |6 ONLINE |7 1 |9 974115 |R 2022-12-28 14:45:12 |a DAIG |b DAIG |l 0 |o Online |r 2022-12-28 |y EB | ||
