Jongseong Jang

607 total citations
20 papers, 350 citations indexed

About

Jongseong Jang is a scholar working on Artificial Intelligence, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jongseong Jang has authored 20 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 8 papers in Biomedical Engineering and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jongseong Jang's work include Soft Robotics and Applications (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Jongseong Jang is often cited by papers focused on Soft Robotics and Applications (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Jongseong Jang collaborates with scholars based in South Korea, Canada and United States. Jongseong Jang's co-authors include Scott Sanner, Zheda Mai, Young Soo Kim, Hyunwoo Kim, Jihwan Jeong, Yee-Suk Kim, Chang Lee, Chulhong Kim, Jeesu Kim and Ruiwen Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Medical Imaging.

In The Last Decade

Jongseong Jang

20 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jongseong Jang South Korea 9 158 119 75 71 34 20 350
Chuanbin Liu China 10 113 0.7× 197 1.7× 47 0.6× 39 0.5× 17 0.5× 34 408
Xiaozheng Xie China 5 131 0.8× 93 0.8× 128 1.7× 34 0.5× 13 0.4× 12 344
Jiangpeng Yan China 10 162 1.0× 182 1.5× 115 1.5× 54 0.8× 6 0.2× 29 444
Xiao-Yun Zhou China 12 104 0.7× 106 0.9× 109 1.5× 164 2.3× 76 2.2× 34 473
Gangming Zhao China 12 167 1.1× 205 1.7× 172 2.3× 23 0.3× 21 0.6× 27 505
Abdelrahman Shaker United Arab Emirates 5 122 0.8× 179 1.5× 65 0.9× 78 1.1× 16 0.5× 8 473
Jiho Choi South Korea 13 93 0.6× 208 1.7× 139 1.9× 32 0.5× 21 0.6× 28 475
Gi-Tae Han South Korea 7 150 0.9× 60 0.5× 204 2.7× 55 0.8× 10 0.3× 11 361
Gerd Reis Germany 12 31 0.2× 188 1.6× 72 1.0× 56 0.8× 19 0.6× 31 486

Countries citing papers authored by Jongseong Jang

Since Specialization
Citations

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

Fields of papers citing papers by Jongseong Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jongseong Jang

This figure shows the co-authorship network connecting the top 25 collaborators of Jongseong Jang. A scholar is included among the top collaborators of Jongseong Jang 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 Jongseong Jang. Jongseong Jang 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.
Jang, Jongseong, et al.. (2024). Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders. Scientific Reports. 14(1). 23199–23199. 5 indexed citations
2.
Li, Ruiwen, Zheda Mai, Zhibo Zhang, Jongseong Jang, & Scott Sanner. (2023). TransCAM: Transformer attention-based CAM refinement for Weakly supervised semantic segmentation. Journal of Visual Communication and Image Representation. 92. 103800–103800. 41 indexed citations
3.
Zhang, Zihan, et al.. (2022). A Pattern-Driven Stochastic Degradation Model for the Prediction of Remaining Useful Life of Rechargeable Batteries. IEEE Transactions on Industrial Informatics. 18(12). 8586–8594. 28 indexed citations
4.
Jang, Jongseong, et al.. (2022). Multi-policy Grounding and Ensemble Policy Learning for Transfer Learning with Dynamics Mismatch. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 3171–3177. 1 indexed citations
5.
Mai, Zheda, et al.. (2021). Online Class-Incremental Continual Learning with Adversarial Shapley Value. Proceedings of the AAAI Conference on Artificial Intelligence. 35(11). 9630–9638. 99 indexed citations
6.
Plataniotis, Konstantinos N., et al.. (2021). Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation. Proceedings of the AAAI Conference on Artificial Intelligence. 35(13). 11639–11647. 21 indexed citations
7.
Plataniotis, Konstantinos N., et al.. (2021). Ada-Sise: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks. 1715–1719. 7 indexed citations
8.
9.
Lee, Chang, Jongseong Jang, Seunghun Lee, et al.. (2020). Classification of femur fracture in pelvic X-ray images using meta-learned deep neural network. Scientific Reports. 10(1). 13694–13694. 38 indexed citations
10.
Lee, Chang, et al.. (2019). Three-dimensional analysis of acetabular orientation using a semi-automated algorithm. SHILAP Revista de lepidopterología. 24(1). 18–25. 8 indexed citations
11.
Lee, Chang, Yee-Suk Kim, Young Soo Kim, & Jongseong Jang. (2019). Automatic Disease Annotation From Radiology Reports Using Artificial Intelligence Implemented by a Recurrent Neural Network. American Journal of Roentgenology. 212(4). 734–740. 23 indexed citations
12.
Jang, Jongseong, et al.. (2017). Real-time Triple-modal Photoacoustic, Ultrasound, and Magnetic Resonance Fusion Imaging of Humans. IEEE Transactions on Medical Imaging. 36(9). 1912–1921. 42 indexed citations
13.
Jang, Jongseong, et al.. (2017). Photoacoustic image-guided navigation system for surgery (Conference Presentation). 13–13. 1 indexed citations
14.
Lee, Chang, Yee-Suk Kim, Hyung Wook Kim, Young Soo Kim, & Jongseong Jang. (2017). A robust method to extract the anterior pelvic plane from CT volume independent of pelvic pose. PubMed. 22(1). 20–26. 2 indexed citations
15.
Jang, Jongseong, et al.. (2016). Virtual wall–based haptic-guided teleoperated surgical robotic system for single-port brain tumor removal surgery. Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine. 231(1). 3–19. 9 indexed citations
16.
Jang, Jongseong, et al.. (2015). Experimental study on restricting the robotic end-effector inside a lesion for safe telesurgery. Minimally Invasive Therapy & Allied Technologies. 24(6). 317–325. 1 indexed citations
17.
Jang, Jongseong, Hyung Wook Kim, & Young Soo Kim. (2014). Construction and verification of a safety region for brain tumor removal with a telesurgical robot system. Minimally Invasive Therapy & Allied Technologies. 23(6). 333–340. 5 indexed citations
18.
Jang, Jongseong, Hyung Wook Kim, & Young Soo Kim. (2014). Co-segmentation of inter-subject brain magnetic resonance images. 2. 80–84. 1 indexed citations
19.
Jang, Jongseong, et al.. (2013). Implementation of LabVIEW®-based Joint-Linear Motion Blending on a Lab-manufactured 6-Axis Articulated Robot (RS2). Journal of The Korean Society of Manufacturing Technology Engineers. 22(2). 318–323. 2 indexed citations
20.
Jang, Jongseong & Young Soo Kim. (2013). Safety management algorithm for telesurgical robot system for brain tumor surgery. 1–2. 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.

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