Youngbae Hwang

1.3k total citations
66 papers, 802 citations indexed

About

Youngbae Hwang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Gastroenterology. According to data from OpenAlex, Youngbae Hwang has authored 66 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Computer Vision and Pattern Recognition, 17 papers in Media Technology and 12 papers in Gastroenterology. Recurrent topics in Youngbae Hwang's work include Advanced Vision and Imaging (20 papers), Image Enhancement Techniques (16 papers) and Advanced Image and Video Retrieval Techniques (13 papers). Youngbae Hwang is often cited by papers focused on Advanced Vision and Imaging (20 papers), Image Enhancement Techniques (16 papers) and Advanced Image and Video Retrieval Techniques (13 papers). Youngbae Hwang collaborates with scholars based in South Korea, United States and Canada. Youngbae Hwang's co-authors include Seon Joo Kim, Yasuyuki Matsushita, Seonghyeon Nam, In So Kweon, Jun‐Hyung Kim, Yun Jeong Lim, In-So Kweon, Junseok Park, Joon‐Young Lee and Jun-Sik Kim and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.

In The Last Decade

Youngbae Hwang

62 papers receiving 772 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Youngbae Hwang South Korea 14 520 230 117 98 78 66 802
Yoshito Mekada Japan 13 319 0.6× 64 0.3× 70 0.6× 25 0.3× 42 0.5× 64 575
K. Vijayan Asari United States 10 239 0.5× 82 0.4× 36 0.3× 52 0.5× 36 0.5× 41 420
Yasin Almalıoğlu United Kingdom 10 342 0.7× 37 0.2× 62 0.5× 362 3.7× 44 0.6× 15 743
Bisser Raytchev Japan 13 367 0.7× 40 0.2× 61 0.5× 84 0.9× 403 5.2× 78 922
J.P. Helferty United States 12 285 0.5× 30 0.1× 24 0.2× 152 1.6× 27 0.3× 24 506
Elli Angelopoulou Germany 18 1.1k 2.1× 305 1.3× 14 0.1× 105 1.1× 11 0.1× 59 1.5k
Yong Ding China 17 429 0.8× 140 0.6× 5 0.0× 138 1.4× 44 0.6× 97 891
Huaici Zhao China 13 275 0.5× 29 0.1× 25 0.2× 111 1.1× 25 0.3× 41 415
Franck Marzani France 14 155 0.3× 61 0.3× 9 0.1× 55 0.6× 123 1.6× 57 569
Changhao Sun China 13 405 0.8× 118 0.5× 12 0.1× 14 0.1× 134 1.7× 23 1.0k

Countries citing papers authored by Youngbae Hwang

Since Specialization
Citations

This map shows the geographic impact of Youngbae Hwang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Youngbae Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youngbae Hwang more than expected).

Fields of papers citing papers by Youngbae Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Youngbae Hwang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Youngbae Hwang. The network helps show where Youngbae Hwang may publish in the future.

Co-authorship network of co-authors of Youngbae Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Youngbae Hwang. A scholar is included among the top collaborators of Youngbae Hwang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Youngbae Hwang. Youngbae Hwang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Hwang, Youngbae, et al.. (2024). Tomato pose estimation using the association of tomato body and sepal. Computers and Electronics in Agriculture. 221. 108961–108961. 6 indexed citations
2.
Hwang, Youngbae, et al.. (2024). Pruning networks at once via nuclear norm-based regularization and bi-level optimization. Computer Vision and Image Understanding. 251. 104247–104247.
3.
Kim, Dongmin, et al.. (2023). Video Analysis of Small Bowel Capsule Endoscopy Using a Transformer Network. Diagnostics. 13(19). 3133–3133. 1 indexed citations
4.
Lee, Eunho, et al.. (2023). Lossless Reconstruction of Convolutional Neural Network for Channel-Based Network Pruning. Sensors. 23(4). 2102–2102. 2 indexed citations
5.
Kim, Sang Hoon, et al.. (2023). The Advent of Domain Adaptation into Artificial Intelligence for Gastrointestinal Endoscopy and Medical Imaging. Diagnostics. 13(19). 3023–3023. 6 indexed citations
6.
Hwang, Youngbae, et al.. (2022). Image classification using DETR based object-level feature. 2022 22nd International Conference on Control, Automation and Systems (ICCAS). 1297–1300. 1 indexed citations
7.
Park, Junseok, Youngbae Hwang, Hyun Gun Kim, et al.. (2022). Reduced detection rate of artificial intelligence in images obtained from untrained endoscope models and improvement using domain adaptation algorithm. Frontiers in Medicine. 9. 1036974–1036974. 3 indexed citations
8.
Kim, Jun‐Hyung & Youngbae Hwang. (2022). GAN-Based Synthetic Data Augmentation for Infrared Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–12. 60 indexed citations
9.
10.
Kim, Seong‐heum & Youngbae Hwang. (2021). A Survey on Deep Learning Based Methods and Datasets for Monocular 3D Object Detection. Electronics. 10(4). 517–517. 26 indexed citations
11.
Nam, Seung‐Joo, Yun Jeong Lim, Ji Hyung Nam, et al.. (2020). 3D reconstruction of small bowel lesions using stereo camera-based capsule endoscopy. Scientific Reports. 10(1). 6025–6025. 21 indexed citations
12.
Choi, Ouk, et al.. (2020). Iterative K-Closest Point Algorithms for Colored Point Cloud Registration. Sensors. 20(18). 5331–5331. 11 indexed citations
13.
Park, Junseok, Youngbae Hwang, Ji Hyung Nam, et al.. (2020). Artificial intelligence that determines the clinical significance of capsule endoscopy images can increase the efficiency of reading. PLoS ONE. 15(10). e0241474–e0241474. 22 indexed citations
14.
Lee, Min‐Ho, et al.. (2020). Gaze+Gesture Interface: Considering Social Acceptability. 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). 5 indexed citations
15.
Park, Junseok, et al.. (2019). Recent Development of Computer Vision Technology to Improve Capsule Endoscopy. Clinical Endoscopy. 52(4). 328–333. 19 indexed citations
16.
Hwang, Youngbae, et al.. (2018). Automatic Sketch Colorization using DCGAN. International Conference on Control, Automation and Systems. 7 indexed citations
17.
Hwang, Youngbae, Junseok Park, Yun Jeong Lim, & Hoon Jai Chun. (2018). Application of Artificial Intelligence in Capsule Endoscopy: Where Are We Now?. Clinical Endoscopy. 51(6). 547–551. 29 indexed citations
18.
Hwang, Youngbae, et al.. (2011). Color correction without color patterns for stereoscopic camera systems. International Conference on Control, Automation and Systems. 1130–1135. 7 indexed citations
19.
Hwang, Youngbae, Jun‐Sik Kim, & In So Kweon. (2011). Difference-Based Image Noise Modeling Using Skellam Distribution. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(7). 1329–1341. 20 indexed citations
20.
Kweon, In-So, et al.. (2005). Silhouette Extraction for Visual Hull Reconstruction.. 339. 39–42. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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