Il-Seok Oh

2.6k total citations · 1 hit paper
61 papers, 1.8k citations indexed

About

Il-Seok Oh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Il-Seok Oh has authored 61 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Vision and Pattern Recognition, 20 papers in Artificial Intelligence and 6 papers in Media Technology. Recurrent topics in Il-Seok Oh's work include Handwritten Text Recognition Techniques (12 papers), Neural Networks and Applications (8 papers) and Image Retrieval and Classification Techniques (7 papers). Il-Seok Oh is often cited by papers focused on Handwritten Text Recognition Techniques (12 papers), Neural Networks and Applications (8 papers) and Image Retrieval and Classification Techniques (7 papers). Il-Seok Oh collaborates with scholars based in South Korea, Canada and China. Il-Seok Oh's co-authors include Jin-Seon Lee, Byung-Ro Moon, Kanghan Oh, Ching Y. Suen, Young-Won Kim, Young‐Chul Chung, Woo‐Sung Kim, Ko Woon Kim, Daewoo Lee and Woo‐Sung Kim and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Access.

In The Last Decade

Il-Seok Oh

54 papers receiving 1.6k citations

Hit Papers

Hybrid genetic algorithms for feature selection 2004 2026 2011 2018 2004 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Il-Seok Oh South Korea 16 780 679 151 141 137 61 1.8k
Abdelmgeid A. Ali Egypt 18 645 0.8× 385 0.6× 122 0.8× 102 0.7× 74 0.5× 33 1.5k
Yuqing Song China 21 358 0.5× 597 0.9× 101 0.7× 119 0.8× 72 0.5× 138 1.3k
Fuqian Shi China 23 301 0.4× 445 0.7× 125 0.8× 287 2.0× 63 0.5× 76 1.5k
Murat Karabatak Türkiye 13 702 0.9× 306 0.5× 101 0.7× 123 0.9× 47 0.3× 77 1.4k
Ahmed M. Anter Egypt 18 463 0.6× 307 0.5× 124 0.8× 103 0.7× 73 0.5× 52 1.1k
Stefano Cagnoni Italy 23 631 0.8× 522 0.8× 38 0.3× 315 2.2× 175 1.3× 116 1.8k
Peishu Wu China 18 442 0.6× 572 0.8× 67 0.4× 96 0.7× 67 0.5× 39 1.4k
AKM Azad Australia 19 364 0.5× 272 0.4× 138 0.9× 122 0.9× 47 0.3× 86 1.4k
Nagwan Abdel Samee Saudi Arabia 20 617 0.8× 348 0.5× 232 1.5× 72 0.5× 85 0.6× 101 1.3k
Ali Thabet Saudi Arabia 13 643 0.8× 709 1.0× 47 0.3× 77 0.5× 44 0.3× 26 1.6k

Countries citing papers authored by Il-Seok Oh

Since Specialization
Citations

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

Fields of papers citing papers by Il-Seok Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Il-Seok Oh. 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 Il-Seok Oh. The network helps show where Il-Seok Oh may publish in the future.

Co-authorship network of co-authors of Il-Seok Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Il-Seok Oh. A scholar is included among the top collaborators of Il-Seok Oh 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 Il-Seok Oh. Il-Seok Oh 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.
Oh, Il-Seok, et al.. (2024). Gripping Success Metric for Robotic Fruit Harvesting. Sensors. 25(1). 181–181. 3 indexed citations
2.
Yoo, Tae Gon, et al.. (2024). Automated volumetric analysis of the inner ear fluid space from hydrops magnetic resonance imaging using 3D neural networks. Scientific Reports. 14(1). 24798–24798. 1 indexed citations
3.
Gu, Jia, et al.. (2024). RAMIS: Increasing robustness and accuracy in medical image segmentation with hybrid CNN-transformer synergy. Neurocomputing. 618. 129009–129009. 2 indexed citations
4.
Lee, Seul Ki, et al.. (2023). Apple detection dataset with visibility and deep learning detectionusing adaptive heatmap regression. 12(10). 19–28. 1 indexed citations
5.
Oh, Kanghan, Il-Seok Oh, Jie Shen, et al.. (2022). Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach. BMC Neuroscience. 23(1). 5–5. 13 indexed citations
6.
Oh, Il-Seok, et al.. (2022). Effectiveness of Human–Artificial Intelligence Collaboration in Cephalometric Landmark Detection. Journal of Personalized Medicine. 12(3). 387–387. 28 indexed citations
7.
Oh, Kanghan, Young‐Chul Chung, Ko Woon Kim, Woo‐Sung Kim, & Il-Seok Oh. (2020). Author Correction: Classification and Visualization of Alzheimer’s Disease using Volumetric Convolutional Neural Network and Transfer Learning. Scientific Reports. 10(1). 5663–5663. 9 indexed citations
8.
Kim, Yumi, et al.. (2020). SVM-based waist circumference estimation using Kinect. Computer Methods and Programs in Biomedicine. 191. 105418–105418. 9 indexed citations
9.
Oh, Kanghan, Sungchan Kim, & Il-Seok Oh. (2020). Salient Explanation for Fine-Grained Classification. IEEE Access. 8. 61433–61441. 4 indexed citations
10.
Oh, Kanghan, Young‐Chul Chung, Ko Woon Kim, Woo‐Sung Kim, & Il-Seok Oh. (2019). Classification and Visualization of Alzheimer’s Disease using Volumetric Convolutional Neural Network and Transfer Learning. Scientific Reports. 9(1). 18150–18150. 222 indexed citations
11.
Oh, Kanghan, et al.. (2019). Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization. Schizophrenia Research. 212. 186–195. 57 indexed citations
12.
Oh, Il-Seok, et al.. (2008). Estimation of rapid-motion for mobile devices using temporal coherence. 6507. 1–6. 1 indexed citations
13.
Lee, Chil-Woo, et al.. (2007). Staff-Line Detection and Removal Algorithm for a Camera-Based Recognition of Music Score Images. IEICE Technical Report; IEICE Tech. Rep.. 107(281). 141–147. 2 indexed citations
14.
Kim, Young-Won & Il-Seok Oh. (2007). Coarse-to-fine Classifier Ensemble Selection using Clustering and Genetic Algorithms. Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong. 34(9). 857–868.
15.
Kim, Young-Won, et al.. (2005). Performance comparison of SVM and neural networks for large-set classification problems. The KIPS Transactions PartB. 12B(1). 25–30. 1 indexed citations
16.
Kim, Young-Won & Il-Seok Oh. (2004). Watermarking text document images using edge direction histograms. Pattern Recognition Letters. 25(11). 1243–1251. 52 indexed citations
17.
Oh, Il-Seok, Jin-Seon Lee, & Byung-Ro Moon. (2004). Hybrid genetic algorithms for feature selection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(11). 1424–1437. 679 indexed citations breakdown →
18.
Oh, Il-Seok & Ching Y. Suen. (2002). A class-modular feedforward neural network for handwriting recognition. Pattern Recognition. 35(1). 229–244. 63 indexed citations
19.
Kim, Hye-Geum, Jinho Yang, Jinseok Lee, & Il-Seok Oh. (2001). Image-based Retrieval of Printed Korean Words using Wavelets. Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong. 28(2). 91–103.
20.
Oh, Il-Seok. (1992). Segmentation of cylindrical parts stored in a bin. Microprocessing and Microprogramming. 33(5). 289–298.

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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