Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Jong-Eun Ha"'
Autor:
Sang-Min Park, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 12, Pp 141594-141603 (2024)
3D semantic scene completion (SSC) aims to get a dense semantic understanding of an environment in 3D. It requires a geometric and semantic knowledge of the surrounding environment and the filling of void areas. In this paper, we propose an improved
Externí odkaz:
https://doaj.org/article/01f886f61c7f4412b4803db67d41bb92
Autor:
Yao Wang, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 12, Pp 129498-129510 (2024)
DETR first used a transformer in object detection. It does not use anchor boxes and non-maximum suppression by converting object detection into a set prediction problem. DETR has shown competitive results on public datasets and brought many new ideas
Externí odkaz:
https://doaj.org/article/fec7b40783624fa6a8ff086bec09824c
Autor:
Keong-Hun Choi, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 12, Pp 121915-121931 (2024)
Object detection is an essential step in various applications. After deep learning appeared, convolutional neural networks or transformers have shown significant improvement in object detection compared to statistically motivated algorithms. But, the
Externí odkaz:
https://doaj.org/article/241b28f7d7984bd1a4154595a4ee32bf
Autor:
Jae-Yeul Kim, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 11, Pp 145551-145565 (2023)
Visual surveillance requires robust detection of foreground objects under challenging environments of abrupt lighting variation, stationary foreground objects, dynamic background objects, and severe weather conditions. Most classical algorithms lever
Externí odkaz:
https://doaj.org/article/0cee51602ba44baf89c00ab6a86020fe
Autor:
Jae-Yeul Kim, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 11, Pp 76904-76912 (2023)
Extrinsic calibration of a 2D camera and a 2D LiDAR is necessary to fuse information from two sensors by representing the information under the same frame. Various geometric constraints such as point-plane, point-line, and point-point are used for th
Externí odkaz:
https://doaj.org/article/6709f06cc7cc47c498ecc2f746591b44
Publikováno v:
IEEE Access, Vol 11, Pp 67460-67467 (2023)
In this paper, we propose a method to improve image classification performance using the fusion of CNN and transformer structure. In the case of CNN, information about a local area on an image can be extracted well, but global information extraction
Externí odkaz:
https://doaj.org/article/f09dd9249dd447f39d73ee2547e94916
Autor:
Keong-Hun Choi, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 11, Pp 67058-67069 (2023)
We propose a method to automatically select proper values of three thresholds in the Canny edge algorithm. Edge detection is widely used for object recognition, detection, and segmentation. Due to its good performance, the Canny edge algorithm is sti
Externí odkaz:
https://doaj.org/article/daebb686206d4071b23f44b10fa2d343
Autor:
Yao Wang, Jong-Eun Ha
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 353 (2024)
In object detection, Transformer-based models such as DETR have exhibited state-of-the-art performance, capitalizing on the attention mechanism to handle spatial relations and feature dependencies. One inherent challenge these models face is the inte
Externí odkaz:
https://doaj.org/article/c2ffaf254ab945a89dc9641f422f2e45
Autor:
Jae-Yeul Kim, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 10, Pp 122857-122869 (2022)
Object detection generally shows promising results only using spatial information, but foreground object detection in visual surveillance requires proper use of temporal information in addition to spatial information. Recently, deep learning-based vi
Externí odkaz:
https://doaj.org/article/a9864dd956f94114a4ed08c4489f161e
Autor:
Jae-Yeul Kim, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 10, Pp 105726-105733 (2022)
In visual surveillance, deep learning-based foreground object detection algorithms are superior to classical background subtraction (BGS)-based algorithms. However, deep learning-based methods are limited because detection performance deteriorates in
Externí odkaz:
https://doaj.org/article/b71acd45be0f4b54bdeb61ad0d0bb648