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pro vyhledávání: '"KIM, Kyung-Soo"'
This paper presents a novel design for a compact, lightweight 6-axis force/torque sensor intended for use in legged robots. The design promotes easy manufacturing and cost reduction, while introducing innovative calibration methods that simplify the
Externí odkaz:
http://arxiv.org/abs/2309.04720
Self-supervised multi-frame depth estimation achieves high accuracy by computing matching costs of pixel correspondences between adjacent frames, injecting geometric information into the network. These pixel-correspondence candidates are computed bas
Externí odkaz:
http://arxiv.org/abs/2304.03560
The limited dynamic range of commercial compact camera sensors results in an inaccurate representation of scenes with varying illumination conditions, adversely affecting image quality and subsequently limiting the performance of underlying image pro
Externí odkaz:
http://arxiv.org/abs/2204.01795
Semantic segmentation algorithms require access to well-annotated datasets captured under diverse illumination conditions to ensure consistent performance. However, poor visibility conditions at varying illumination conditions result in laborious and
Externí odkaz:
http://arxiv.org/abs/2202.13144
Autor:
Bangunharcana, Antyanta, Cho, Jae Won, Lee, Seokju, Kweon, In So, Kim, Kyung-Soo, Kim, Soohyun
Volumetric deep learning approach towards stereo matching aggregates a cost volume computed from input left and right images using 3D convolutions. Recent works showed that utilization of extracted image features and a spatially varying cost volume a
Externí odkaz:
http://arxiv.org/abs/2108.05773
Region modification-based data augmentation techniques have shown to improve performance for high level vision tasks (object detection, semantic segmentation, image classification, etc.) by encouraging underlying algorithms to focus on multiple discr
Externí odkaz:
http://arxiv.org/abs/2103.05889
Presence of haze in images obscures underlying information, which is undesirable in applications requiring accurate environment information. To recover such an image, a dehazing algorithm should localize and recover affected regions while ensuring co
Externí odkaz:
http://arxiv.org/abs/2101.10449
Poor image quality in low light images may result in a reduced number of feature matching between images. In this paper, we investigate the performance of feature extraction algorithms in low light environments. To find an optimal setting to retain f
Externí odkaz:
http://arxiv.org/abs/2009.00842
Autor:
Lee, Hae Ryong1 (AUTHOR) skybandpeter@daum.net, Kim, Kyung Soo2 (AUTHOR), Min, Hyun Jin2 (AUTHOR) jjinient@cau.ac.kr
Publikováno v:
Life (2075-1729). Jan2024, Vol. 14 Issue 1, p75. 10p.
Publikováno v:
In Kidney International October 2023 104(4):820-827