Ho Bae

510 total citations
14 papers, 266 citations indexed

About

Ho Bae is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Ho Bae has authored 14 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Signal Processing. Recurrent topics in Ho Bae's work include Adversarial Robustness in Machine Learning (4 papers), Advanced Steganography and Watermarking Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Ho Bae is often cited by papers focused on Adversarial Robustness in Machine Learning (4 papers), Advanced Steganography and Watermarking Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Ho Bae collaborates with scholars based in South Korea and Puerto Rico. Ho Bae's co-authors include Sungroh Yoon, Sunyoung Kwon, Hyun-Soo Choi, Seonwoo Min, Yo-Han Kim, Uiwon Hwang, Chang‐Ho Yun, Yunheung Paek, Siwon Kim and Jaekoo Lee and has published in prestigious journals such as IEEE Access, Sensors and BMC Bioinformatics.

In The Last Decade

Ho Bae

12 papers receiving 256 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ho Bae South Korea 7 111 74 64 30 23 14 266
Zhaoxian Zhou United States 9 135 1.2× 95 1.3× 95 1.5× 73 2.4× 20 0.9× 35 416
Jian Jiang China 11 93 0.8× 68 0.9× 45 0.7× 23 0.8× 5 0.2× 35 280
Wenxuan Wang China 8 124 1.1× 140 1.9× 100 1.6× 12 0.4× 81 3.5× 26 507
Limeng Pu United States 12 211 1.9× 215 2.9× 38 0.6× 17 0.6× 17 0.7× 27 419
Jianqiang Chen China 10 52 0.5× 123 1.7× 85 1.3× 18 0.6× 11 0.5× 19 305
Blaž Škrlj Slovenia 13 70 0.6× 106 1.4× 177 2.8× 20 0.7× 12 0.5× 40 393
Jintao Meng China 8 67 0.6× 124 1.7× 47 0.7× 26 0.9× 11 0.5× 36 284
Pavel Karpov Russia 10 247 2.2× 145 2.0× 76 1.2× 22 0.7× 45 2.0× 22 427

Countries citing papers authored by Ho Bae

Since Specialization
Citations

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

Fields of papers citing papers by Ho Bae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ho Bae

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

All Works

14 of 14 papers shown
1.
Bae, Ho. (2024). Evaluation of Malware Classification Models for Heterogeneous Data. Sensors. 24(1). 288–288. 3 indexed citations
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Bae, Ho, et al.. (2022). Data Embedding Scheme for Efficient Program Behavior Modeling With Neural Networks. IEEE Transactions on Emerging Topics in Computational Intelligence. 6(4). 982–993. 2 indexed citations
5.
Bae, Ho, et al.. (2021). Learn2Evade: Learning-Based Generative Model for Evading PDF Malware Classifiers. IEEE Transactions on Artificial Intelligence. 2(4). 299–313. 11 indexed citations
6.
Bae, Ho, et al.. (2021). PixelSteganalysis: Pixel-Wise Hidden Information Removal With Low Visual Degradation. IEEE Transactions on Dependable and Secure Computing. 20(1). 331–342. 15 indexed citations
7.
Bae, Ho, et al.. (2020). Gradient Masking of Label Smoothing in Adversarial Robustness. IEEE Access. 9. 6453–6464. 20 indexed citations
8.
Bae, Ho, Seonwoo Min, Hyun-Soo Choi, & Sungroh Yoon. (2020). DNA Privacy: Analyzing Malicious DNA Sequences Using Deep Neural Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(2). 888–898. 11 indexed citations
9.
Lee, Jaekoo, Ho Bae, & Sungroh Yoon. (2020). Anomaly Detection by Learning Dynamics From a Graph. IEEE Access. 8. 64356–64365. 4 indexed citations
10.
Choi, Hyun-Soo, Seonwoo Min, Siwon Kim, et al.. (2019). Learning-Based Instantaneous Drowsiness Detection Using Wired and Wireless Electroencephalography. IEEE Access. 7. 146390–146402. 18 indexed citations
11.
Kwon, Sunyoung, et al.. (2019). Comprehensive ensemble in QSAR prediction for drug discovery. BMC Bioinformatics. 20(1). 521–521. 156 indexed citations
12.
Bae, Ho, et al.. (2019). AnomiGAN: Generative Adversarial Networks for Anonymizing Private Medical Data. PubMed. 25. 563–574. 16 indexed citations
13.
Bae, Ho, Byunghan Lee, Sunyoung Kwon, & Sungroh Yoon. (2018). DNA Steganalysis Using Deep Recurrent Neural Networks. PubMed. 24. 88–99. 5 indexed citations
14.
Park, Seongsik, et al.. (2018). Quantized Memory-Augmented Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 5 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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