Woohyung Lim

1.5k total citations · 1 hit paper
14 papers, 933 citations indexed

About

Woohyung Lim is a scholar working on Artificial Intelligence, Signal Processing and Oncology. According to data from OpenAlex, Woohyung Lim has authored 14 papers receiving a total of 933 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Signal Processing and 5 papers in Oncology. Recurrent topics in Woohyung Lim's work include Speech and Audio Processing (6 papers), Speech Recognition and Synthesis (6 papers) and Cutaneous Melanoma Detection and Management (5 papers). Woohyung Lim is often cited by papers focused on Speech and Audio Processing (6 papers), Speech Recognition and Synthesis (6 papers) and Cutaneous Melanoma Detection and Management (5 papers). Woohyung Lim collaborates with scholars based in South Korea and United States. Woohyung Lim's co-authors include Sung Eun Chang, Seung Seog Han, Ilwoo Park, Myoung Shin Kim, Gyeong‐Hun Park, Jung‐Im Na, Jung Im Na, Chang‐Hun Huh, Seong Hwan Kim and Ik Jun Moon and has published in prestigious journals such as PLoS ONE, PLoS Medicine and IEEE Access.

In The Last Decade

Woohyung Lim

12 papers receiving 882 citations

Hit Papers

align trajectories

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.

Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm

2018 446 citations Seung Seog Han, Myoung Shin Kim et al. Journal of Investigative Dermatology profile →

Peers

Woohyung Lim

ONCOL

AI

EPIDE

RNMI

DERMA

Stefan Fröhling Germany

Brian Helba United States

David Gutman United States

Achim Hekler Germany

Ferdinand Toberer Germany

Catarina Barata Portugal

Konstantinos Liopyris United States

Rusong Meng China

Manu Goyal United Kingdom

Ahmad Naeem Pakistan

Stefan Fröhling Germany

Woohyung Lim

500 ×0.8

ONCOL

467 ×0.9

AI

168 ×0.7

EPIDE

163 ×1.3

RNMI

73 ×0.6

DERMA

Citations per year, relative to Woohyung Lim Woohyung Lim (= 1×) peers Stefan Fröhling

Countries citing papers authored by Woohyung Lim

Since Specialization

Citations

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

Fields of papers citing papers by Woohyung Lim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Woohyung Lim

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

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

1.

Park, Soyeon, et al.. (2025). On Incorporating Prior Knowledge Extracted From Large Language Models Into Causal Discovery. IEEE Access. 13. 194691–194713. 1 indexed citations

2.

Lee, Kyung‐Eun, et al.. (2025). Representation Space Augmentation for Effective Self-Supervised Learning on Tabular Data. Proceedings of the AAAI Conference on Artificial Intelligence. 39(11). 11625–11633.

3.

Kim, Jung-Hee, et al.. (2023). Multi-Resolution Sequence Aggregation and Model-Agnostic Framework for Time-Series Forecasting. 32. 1–5. 1 indexed citations

4.

Han, Seung Seog, Ik Jun Moon, Seong Hwan Kim, et al.. (2020). Assessment of deep neural networks for the diagnosis of benign and malignant skin neoplasms in comparison with dermatologists: A retrospective validation study. PLoS Medicine. 17(11). e1003381–e1003381. 31 indexed citations

5.

Han, Seung Seog, Ilwoo Park, Sung Eun Chang, et al.. (2020). Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. Journal of Investigative Dermatology. 140(9). 1753–1761. 145 indexed citations

6.

Han, Seung Seog, Ik Jun Moon, Woohyung Lim, et al.. (2019). Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network. JAMA Dermatology. 156(1). 29–29. 95 indexed citations

7.

Lim, Woohyung, et al.. (2019). AIX: A high performance and energy efficient inference accelerator on FPGA for a DNN-based commercial speech recognition. 1495–1500. 2 indexed citations

8.

Han, Seung Seog, Myoung Shin Kim, Woohyung Lim, et al.. (2018). Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm. Journal of Investigative Dermatology. 138(7). 1529–1538. 446 indexed citations breakdown →

9.

Han, Seung Seog, Gyeong‐Hun Park, Woohyung Lim, et al.. (2018). Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network. PLoS ONE. 13(1). e0191493–e0191493. 187 indexed citations

10.

Lim, Woohyung, Chang Woo Han, Jong Won Shin, & Nam Soo Kim. (2008). Cepstral domain feature compensation based on diagonal approximation. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. 4401–4404. 3 indexed citations

11.

Lim, Woohyung, et al.. (2007). Speech reinforcement based on partial specific loudness. 978–981. 6 indexed citations

12.

Kim, Nam Soo, et al.. (2005). An approach to robust unsupervised speaker adaptation. IEEE Signal Processing Letters. 12(6). 469–472. 1 indexed citations

13.

Kim, Nam Soo, Woohyung Lim, & Richard M. Stern. (2005). Feature compensation based on switching linear dynamic model. IEEE Signal Processing Letters. 12(6). 473–476. 15 indexed citations

14.

Kim, Young Joon, Hyun Woo Kim, Woohyung Lim, & Nam Soo Kim. (2003). Feature compensation technique for robust speech recognition in noisy environments. 357–360.

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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