Jihwan Bang

441 total citations · 1 hit paper
5 papers, 253 citations indexed

About

Jihwan Bang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, Jihwan Bang has authored 5 papers receiving a total of 253 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 0 papers in Infectious Diseases. Recurrent topics in Jihwan Bang's work include Domain Adaptation and Few-Shot Learning (4 papers), Multimodal Machine Learning Applications (3 papers) and Advanced Neural Network Applications (2 papers). Jihwan Bang is often cited by papers focused on Domain Adaptation and Few-Shot Learning (4 papers), Multimodal Machine Learning Applications (3 papers) and Advanced Neural Network Applications (2 papers). Jihwan Bang collaborates with scholars based in South Korea. Jihwan Bang's co-authors include Youngjoon Yoo, Jonghyun Choi, Jung-Woo Ha, Hwanjun Song, Hyojin Park, Nojun Kwak, Dongyoon Han, Seulki Park and Jae-Gil Lee and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Seoul National University Open Repository (Seoul National University).

In The Last Decade

Jihwan Bang

5 papers receiving 248 citations

Hit Papers

Rainbow Memory: Continual Learning with a Memory of Diver... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Rainbow Memory: Continual Learning with a Memory of Diverse Samples
    2021 197 citations Jihwan Bang, Youngjoon Yoo et al. profile →

Peers

Jihwan Bang
Kaixiong Gong China
Vincent Perot United States
Yen-Chang Hsu United States
Jaehyung Kim South Korea
Qiushan Guo China
Linjun Zhou China
Jaemin Na South Korea
Eugene Belilovsky Canada
Vikas Verma Finland
Raphael Gontijo Lopes United States
Kaixiong Gong China
Jihwan Bang
Citations per year, relative to Jihwan Bang Jihwan Bang (= 1×) peers Kaixiong Gong

Countries citing papers authored by Jihwan Bang

Since Specialization
Citations

This map shows the geographic impact of Jihwan Bang'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 Jihwan Bang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jihwan Bang more than expected).

Fields of papers citing papers by Jihwan Bang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jihwan Bang. 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 Jihwan Bang. The network helps show where Jihwan Bang may publish in the future.

Co-authorship network of co-authors of Jihwan Bang

This figure shows the co-authorship network connecting the top 25 collaborators of Jihwan Bang. A scholar is included among the top collaborators of Jihwan Bang 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 Jihwan Bang. Jihwan Bang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
1.
Bang, Jihwan, et al.. (2024). Active Prompt Learning in Vision Language Models. 26994–27004. 2 indexed citations
2.
Han, Dongyoon, et al.. (2023). Generating Instance-level Prompts for Rehearsal-free Continual Learning. 11813–11823. 15 indexed citations
3.
Bang, Jihwan, et al.. (2022). Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9265–9274. 16 indexed citations
4.
Bang, Jihwan, et al.. (2021). Rainbow Memory: Continual Learning with a Memory of Diverse Samples. 8214–8223. 197 indexed citations breakdown →
5.
Park, Hyojin, et al.. (2020). SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder. Seoul National University Open Repository (Seoul National University). 2055–2063. 23 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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2026