Sanghoon Jun

1.9k total citations · 1 hit paper
27 papers, 1.2k citations indexed

About

Sanghoon Jun is a scholar working on Civil and Structural Engineering, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Sanghoon Jun has authored 27 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Civil and Structural Engineering, 9 papers in Computer Vision and Pattern Recognition and 9 papers in Signal Processing. Recurrent topics in Sanghoon Jun's work include Water Systems and Optimization (9 papers), Music and Audio Processing (9 papers) and Music Technology and Sound Studies (7 papers). Sanghoon Jun is often cited by papers focused on Water Systems and Optimization (9 papers), Music and Audio Processing (9 papers) and Music Technology and Sound Studies (7 papers). Sanghoon Jun collaborates with scholars based in South Korea, United States and Austria. Sanghoon Jun's co-authors include Joon Beom Seo, Namkug Kim, Guk Bae Kim, Hyunna Lee, June‐Goo Lee, Eenjun Hwang, Seungmin Rho, Kevin Lansey, Jihoon Moon and David A. Lynch and has published in prestigious journals such as Water Resources Management, Journal of Water Resources Planning and Management and Multimedia Tools and Applications.

In The Last Decade

Sanghoon Jun

25 papers receiving 1.2k citations

Hit Papers

Deep Learning in Medical Imaging: General Overview 2017 2026 2020 2023 2017 250 500 750
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. Deep Learning in Medical Imaging: General Overview
    2017 848 citations June‐Goo Lee, Sanghoon Jun et al. Korean Journal of Radiology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sanghoon Jun South Korea 10 487 354 201 191 156 27 1.2k
Lal Hussain Pakistan 24 430 0.9× 647 1.8× 340 1.7× 185 1.0× 160 1.0× 88 1.6k
Narendra D. Londhe India 25 492 1.0× 438 1.2× 256 1.3× 151 0.8× 392 2.5× 125 1.9k
Shan Yang Switzerland 12 466 1.0× 151 0.4× 331 1.6× 227 1.2× 125 0.8× 43 1.1k
Shivajirao M. Jadhav India 15 388 0.8× 474 1.3× 240 1.2× 173 0.9× 77 0.5× 25 1.2k
Tao Tan China 23 1.0k 2.1× 924 2.6× 459 2.3× 258 1.4× 319 2.0× 122 2.0k
Muhammad Owais Pakistan 20 485 1.0× 318 0.9× 428 2.1× 115 0.6× 64 0.4× 94 1.2k
Hong Song China 17 444 0.9× 268 0.8× 562 2.8× 315 1.6× 105 0.7× 182 1.4k
Idit Diamant Israel 11 752 1.5× 868 2.5× 686 3.4× 219 1.1× 152 1.0× 19 1.9k
Anjan Gudigar India 27 952 2.0× 457 1.3× 633 3.1× 243 1.3× 120 0.8× 58 2.0k
Deepak Ranjan Nayak India 26 760 1.6× 908 2.6× 723 3.6× 122 0.6× 97 0.6× 74 2.0k

Countries citing papers authored by Sanghoon Jun

Since Specialization
Citations

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

Fields of papers citing papers by Sanghoon Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sanghoon Jun

This figure shows the co-authorship network connecting the top 25 collaborators of Sanghoon Jun. A scholar is included among the top collaborators of Sanghoon Jun 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 Sanghoon Jun. Sanghoon Jun 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.
Jun, Sanghoon & Donghwi Jung. (2025). Exploration of deep learning leak detection model across multiple smart water distribution systems: Detectable leak sizes with AMI meters. Water Research X. 29. 100332–100332. 4 indexed citations
2.
Jun, Sanghoon, Donghwi Jung, & Kevin Lansey. (2024). Three-dimensional convolutional neural network for leak detection and localization in smart water distribution systems. Water Research X. 25. 100264–100264. 1 indexed citations
3.
Jun, Sanghoon & Kevin Lansey. (2023). Convolutional Neural Network for Burst Detection in Smart Water Distribution Systems. Water Resources Management. 37(9). 3729–3743. 11 indexed citations
4.
Jun, Sanghoon & Kevin Lansey. (2023). Comparison of AMI and SCADA Systems for Leak Detection and Localization in Water Distribution Networks. Journal of Water Resources Planning and Management. 149(11). 8 indexed citations
5.
Jun, Sanghoon & Young Hwan Choi. (2022). Data Generation Approaches to Detect Abnormal Conditions in Water Distribution Systems. Korean Society of Hazard Mitigation. 22(2). 69–79. 1 indexed citations
6.
Jun, Sanghoon, et al.. (2021). Response Surfaces for Water Distribution System Pipe Roughness Calibration. Journal of Water Resources Planning and Management. 148(3). 7 indexed citations
7.
Jun, Sanghoon, Beomhee Park, Joon Beom Seo, Sang‐Min Lee, & Namkug Kim. (2017). Development of a Computer-Aided Differential Diagnosis System to Distinguish Between Usual Interstitial Pneumonia and Non-specific Interstitial Pneumonia Using Texture- and Shape-Based Hierarchical Classifiers on HRCT Images. Journal of Digital Imaging. 31(2). 235–244. 14 indexed citations
8.
Kim, Guk Bae, Kyu-Hwan Jung, Yeha Lee, et al.. (2017). Comparison of Shallow and Deep Learning Methods on Classifying the Regional Pattern of Diffuse Lung Disease. Journal of Digital Imaging. 31(4). 415–424. 81 indexed citations
9.
Jun, Sanghoon, Namkug Kim, Joon Beom Seo, Young Kyung Lee, & David A. Lynch. (2017). An Ensemble Method for Classifying Regional Disease Patterns of Diffuse Interstitial Lung Disease Using HRCT Images from Different Vendors. Journal of Digital Imaging. 30(6). 761–771. 5 indexed citations
10.
Moon, Jihoon, et al.. (2017). Forecasting power consumption for higher educational institutions based on machine learning. The Journal of Supercomputing. 74(8). 3778–3800. 56 indexed citations
11.
Lee, June‐Goo, Sanghoon Jun, Hyunna Lee, et al.. (2017). Deep Learning in Medical Imaging: General Overview. Korean Journal of Radiology. 18(4). 570–570. 848 indexed citations breakdown →
12.
Jun, Sanghoon, Jehyeok Rew, & Eenjun Hwang. (2015). Runner’s Jukebox: A Music Player for Running using Pace Recognition and Music Mixing. 18–22. 1 indexed citations
13.
Kim, Daehoon, Seungmin Rho, Sanghoon Jun, & Eenjun Hwang. (2015). Classification and indexing scheme of large-scale image repository for spatio-temporal landmark recognition. Integrated Computer-Aided Engineering. 22(2). 201–213. 12 indexed citations
14.
Jun, Sanghoon, et al.. (2014). Geographical Region Mapping Scheme Based On Musical Preferences.. Zenodo (CERN European Organization for Nuclear Research). 519–524.
15.
Jun, Sanghoon & Eenjun Hwang. (2013). SmartRadio: Cloning Internet radio broadcasting stations. 16(4). 2701–2709.
16.
Kim, Daehoon, Dae-Yong Kim, Sanghoon Jun, Seungmin Rho, & Eenjun Hwang. (2013). TrendsSummary: a platform for retrieving and summarizing trendy multimedia contents. Multimedia Tools and Applications. 73(2). 857–872. 4 indexed citations
17.
Jun, Sanghoon, Seungmin Rho, & Eenjun Hwang. (2013). Music structure analysis using self-similarity matrix and two-stage categorization. Multimedia Tools and Applications. 74(1). 287–302. 6 indexed citations
18.
Jun, Sanghoon, Seungmin Rho, & Eenjun Hwang. (2010). Music Retrieval and Recommendation Scheme Based on Varying Mood Sequences. International Journal on Semantic Web and Information Systems. 6(2). 1–16. 10 indexed citations
19.
Jun, Sanghoon, et al.. (2009). A Similar Music Retrieval Scheme Based on Musical Mood Variation. 167–172. 4 indexed citations
20.
Rho, Seungmin, et al.. (2009). Music emotion classification and context-based music recommendation. Multimedia Tools and Applications. 47(3). 433–460. 95 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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