Dong-Joong Kang

13 papers C 1Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Disentangled reflectance-ambient feature learning for day-night vehicle re-identification.
Appl. Soft Comput.
Tae-Moon Seo, Dong-Joong Kang
2024 J jnl
Novel method of performance-optimized metastructure design for electromagnetic wave absorption in specific band using deep learning.
Eng. Appl. Artif. Intell.
Han-Ik On, Leekyo Jeong, Tae-Moon Seo, Yehrin Jo, Wonwoo Choi, Dong-Joong Kang, Jun-Hyub Park, Hak-Joo Lee
2023 J jnl
Knowledge Distillation With Feature Self Attention.
IEEE Access
Sin-Gu Park, Dong-Joong Kang
2022 J jnl
A Robust Layout-Independent License Plate Detection and Recognition Model Based on Attention Method.
IEEE Access
Tae-Moon Seo, Dong-Joong Kang
2019 J jnl
Deep attention network for person re-identification with multi-loss.
Comput. Electr. Eng.
Rui Li, Baopeng Zhang, Dong-Joong Kang, Zhu Teng
2019 J jnl
Fast and efficient contrast-enhanced super-resolution without real-world data using concatenated recursive compressor-decompressor network.
IET Image Process.
Jun-Myung Choi, Dong-Joong Kang
2019 J jnl
Unified convolutional neural network for direct facial keypoints detection.
Vis. Comput.
Je-Kang Park, Dong-Joong Kang
2016 J jnl
From sample selection to model update: A robust online visual tracking algorithm against drifting.
Neurocomputing
Zhu Teng, Tao Wang, Feng Liu, Dong-Joong Kang, Congyan Lang, Songhe Feng
2015 — conf
Ellipse detection method based on the advanced three point algorithm.
FCV
Bae-keun Kwon, Dong-Joong Kang
2014 — conf
Regional SVM Classifiers with a Spatial Model for Object Detection.
VISAPP (2)
Zhu Teng, Baopeng Zhang, Onecue Kim, Dong-Joong Kang
2013 — conf
Disjunctive Normal Form of Weak Classifiers for Online Learning based Object Tracking.
VISAPP (2)
Zhu Teng, Dong-Joong Kang
2011 — conf
Ellipse detection using an improved randomized Hough transformation.
Image Processing: Algorithms and Systems
Zhu Teng, Jeong-Hyun Kim, Dong-Joong Kang
2008 C conf
Method to improve the performance of the adaboost algorithm by combining weak classifiers.
CBMI
Jeong-Hyun Kim, Bae-Guen Kwon, Jin-Young Kim, Dong-Joong Kang