Dae Hoe Kim

798 total citations
31 papers, 553 citations indexed

About

Dae Hoe Kim is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dae Hoe Kim has authored 31 papers receiving a total of 553 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dae Hoe Kim's work include AI in cancer detection (21 papers), Image Retrieval and Classification Techniques (9 papers) and Digital Radiography and Breast Imaging (9 papers). Dae Hoe Kim is often cited by papers focused on AI in cancer detection (21 papers), Image Retrieval and Classification Techniques (9 papers) and Digital Radiography and Breast Imaging (9 papers). Dae Hoe Kim collaborates with scholars based in South Korea, Canada and Cyprus. Dae Hoe Kim's co-authors include Yong Man Ro, Wissam J. Baddar, Jinhyeok Jang, Seong Tae Kim, Jae Young Choi, Konstantinos N. Plataniotis, Seung Hyun Lee, Jung Min Chang, Seon Hyeong Choi and Eun Suk and has published in prestigious journals such as Expert Systems with Applications, Physics in Medicine and Biology and Medical Physics.

In The Last Decade

Dae Hoe Kim

29 papers receiving 528 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dae Hoe Kim South Korea 10 319 257 220 100 60 31 553
Qiangchang Wang China 5 273 0.9× 192 0.7× 49 0.2× 32 0.3× 25 0.4× 12 382
Sajid Ali Khan Pakistan 10 268 0.8× 94 0.4× 66 0.3× 24 0.2× 12 0.2× 21 354
Asim Munir Pakistan 10 245 0.8× 37 0.1× 186 0.8× 134 1.3× 5 0.1× 21 486
Tianrong Rao Australia 8 283 0.9× 106 0.4× 183 0.8× 34 0.3× 10 0.2× 19 485
Sheeraz Akram Pakistan 17 176 0.6× 30 0.1× 222 1.0× 237 2.4× 5 0.1× 52 635
Omar Hisham Alsadoon Iraq 11 129 0.4× 38 0.1× 149 0.7× 83 0.8× 6 0.1× 37 375
Yimo Guo China 8 322 1.0× 67 0.3× 64 0.3× 23 0.2× 12 0.2× 14 389
Tanoy Debnath Bangladesh 7 131 0.4× 28 0.1× 222 1.0× 79 0.8× 23 0.4× 12 561
Ling Lo Taiwan 10 221 0.7× 168 0.7× 79 0.4× 12 0.1× 38 0.6× 14 334

Countries citing papers authored by Dae Hoe Kim

Since Specialization
Citations

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

Fields of papers citing papers by Dae Hoe Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae Hoe Kim. 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 Dae Hoe Kim. The network helps show where Dae Hoe Kim may publish in the future.

Co-authorship network of co-authors of Dae Hoe Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Dae Hoe Kim. A scholar is included among the top collaborators of Dae Hoe Kim 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 Dae Hoe Kim. Dae Hoe Kim 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.
2.
Kim, Dae Hoe, Seong Tae Kim, Jung Min Chang, & Yong Man Ro. (2017). Latent feature representation with depth directional long-term recurrent learning for breast masses in digital breast tomosynthesis. Physics in Medicine and Biology. 62(3). 1009–1031. 19 indexed citations
3.
Kim, Dae Hoe, Wissam J. Baddar, & Yong Man Ro. (2016). Micro-Expression Recognition with Expression-State Constrained Spatio-Temporal Feature Representations. 382–386. 141 indexed citations
4.
Baddar, Wissam J., et al.. (2016). A deep facial landmarks detection with facial contour and facial components constraint. 3209–3213. 9 indexed citations
5.
6.
Kim, Dae Hoe, Seong Tae Kim, & Yong Man Ro. (2015). Improving mass detection using combined feature representations from projection views and reconstructed volume of DBT and boosting based classification with feature selection. Physics in Medicine and Biology. 60(22). 8809–8832. 3 indexed citations
7.
Kim, Seong Tae, Dae Hoe Kim, & Yong Man Ro. (2015). Detection of masses in digital breast tomosynthesis using complementary information of simulated projection. Medical Physics. 42(12). 7043–7058. 1 indexed citations
8.
Choi, Jae Young, Dae Hoe Kim, Konstantinos N. Plataniotis, & Yong Man Ro. (2015). Classifier ensemble generation and selection with multiple feature representations for classification applications in computer-aided detection and diagnosis on mammography. Expert Systems with Applications. 46. 106–121. 38 indexed citations
9.
Kim, Dae Hoe, Seong Tae Kim, Wissam J. Baddar, & Yong Man Ro. (2015). Feature extraction from bilateral dissimilarity in digital breast tomosynthesis reconstructed volume. 4521–4524. 2 indexed citations
10.
Baddar, Wissam J., et al.. (2015). Utilizing digital breast tomosynthesis projection views correlation for microcalcification enhancement for detection purposes. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9414. 941421–941421. 1 indexed citations
11.
Kim, Dae Hoe, Jae Young Choi, & Yong Man Ro. (2014). Region based stellate features combined with variable selection using AdaBoost learning in mammographic computer-aided detection. Computers in Biology and Medicine. 63. 238–250. 9 indexed citations
12.
Choi, Jae Young, Dae Hoe Kim, Konstantinos N. Plataniotis, & Yong Man Ro. (2014). Computer-aided detection (CAD) of breast masses in mammography: combined detection and ensemble classification. Physics in Medicine and Biology. 59(14). 3697–3719. 11 indexed citations
13.
Kim, Seong Tae, Dae Hoe Kim, & Yong Man Ro. (2014). Breast mass detection using slice conspicuity in 3D reconstructed digital breast volumes. Physics in Medicine and Biology. 59(17). 5003–5023. 10 indexed citations
14.
Baddar, Wissam J., Dae Hoe Kim, & Yong Man Ro. (2014). Breast tissue removal for enhancing microcalcification cluster detection in mammograms. 363–366.
15.
16.
Kim, Dae Hoe, Jae Young Choi, & Yong Man Ro. (2013). Boosting framework for mammographic mass classification with combination of CC and MLO view information. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8670. 86701V–86701V. 3 indexed citations
17.
Kim, Dae Hoe, Seung Hyun Lee, & Yong Man Ro. (2013). Mass type-specific sparse representation for mass classification in computer-aided detection on mammograms. BioMedical Engineering OnLine. 12(S1). S3–S3. 29 indexed citations
18.
Choi, Jae Young, Dae Hoe Kim, Konstantinos N. Plataniotis, & Yong Man Ro. (2012). Combining multiple feature representations and AdaBoost ensemble learning for reducing false-positive detections in Computer-aided Detection of masses on mammograms. PubMed. 2012. 4394–4397. 4 indexed citations
19.
Kim, Dae Hoe, Jae Young Choi, Seon Hyeong Choi, & Yong Man Ro. (2012). Mammographic enhancement with combining local statistical measures and sliding band filter for improved mass segmentation in mammograms. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8315. 83151Z–83151Z. 6 indexed citations
20.
Kim, Dae Hoe, Jae Young Choi, & Yong Man Ro. (2012). A novel mammographic mass detection approach to combining suprevised and unsuprevised detection algorithms. 212. 2857–2860. 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Qiangchang Wang Breakdown of academic impact, for papers by Sajid Ali Khan Breakdown of academic impact, for papers by Asim Munir Breakdown of academic impact, for papers by Tianrong Rao Breakdown of academic impact, for papers by Sheeraz Akram Breakdown of academic impact, for papers by Omar Hisham Alsadoon Breakdown of academic impact, for papers by Yimo Guo Breakdown of academic impact, for papers by Tanoy Debnath Breakdown of academic impact, for papers by Ling Lo
Rankless by CCL
2026