Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ukcheol Shin"'
Publikováno v:
Machine Vision and Applications. 34
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fcb5ae45d62fe0963a010efd5c50c1f
https://doi.org/10.1007/s00138-023-01404-3
https://doi.org/10.1007/s00138-023-01404-3
Publikováno v:
IEEE Robotics and Automation Letters. 7:1103-1110
A thermal camera can robustly capture thermal radiation images under harsh light conditions such as night scenes, tunnels, and disaster scenarios. However, despite this advantage, neither depth nor ego-motion estimation research for the thermal camer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::198eb01d9ab2775a9c9b1e31573292a6
https://doi.org/10.1109/lra.2021.3137895
https://doi.org/10.1109/lra.2021.3137895
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de528f4f1eaabf3e05ab3bd87d39acaf
https://doi.org/10.1109/wacv56688.2023.00575
https://doi.org/10.1109/wacv56688.2023.00575
Publikováno v:
IEEE Robotics and Automation Letters. 6:6497-6504
In this letter, we propose a multi-spectral unsupervised domain adaptation for thermal image semantic segmentation. The proposed framework aims to address the data scarcity problem and boost segmentation performance in the thermal domain with the hel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e20f032c5073e214a7c6589002ce9702
https://doi.org/10.1109/lra.2021.3093652
https://doi.org/10.1109/lra.2021.3093652
Recently, self-supervised learning of depth and ego-motion from thermal images shows strong robustness and reliability under challenging scenarios. However, the inherent thermal image properties such as weak contrast, blurry edges, and noise hinder t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c0403f467767bbc7335bad7de080f1a
http://arxiv.org/abs/2201.04387
http://arxiv.org/abs/2201.04387
In this paper, we propose a multi-objective camera ISP framework that utilizes Deep Reinforcement Learning (DRL) and camera ISP toolbox that consist of network-based and conventional ISP tools. The proposed DRL-based camera ISP framework iteratively
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d703a0a5d4c822548cbe825cb0d70b73
Publikováno v:
IROS
In this paper, we propose a noise-aware exposure control algorithm for robust robot vision. Our method aims to capture the best-exposed image which can boost the performance of various computer vision and robotics tasks. For this purpose, we carefull
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bdda0057367ae14fa8b07e0252c4fa15
https://doi.org/10.1109/iros40897.2019.8968590
https://doi.org/10.1109/iros40897.2019.8968590
Autor:
Jinsun Park, Francois Rameau, Junhyeok Kim, Dong-Geol Choi, In So Kweon, Kyungdon Joo, Gyumin Shim, Ukcheol Shin
Publikováno v:
IROS
In this paper, we present a multi-camera sensor system along with its control algorithm for automated visual inspection from a moving vehicle. To accomplish this task, we propose a unique hardware configuration consisting of a frontal stereo vision s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b91a81204feb628bc634c5db7aedc28
https://doi.org/10.1109/iros40897.2019.8968085
https://doi.org/10.1109/iros40897.2019.8968085