Jeonghong Kim

721 total citations
27 papers, 416 citations indexed

About

Jeonghong Kim is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Jeonghong Kim has authored 27 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 5 papers in Computer Networks and Communications. Recurrent topics in Jeonghong Kim's work include Advanced Neural Network Applications (7 papers), Anomaly Detection Techniques and Applications (6 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Jeonghong Kim is often cited by papers focused on Advanced Neural Network Applications (7 papers), Anomaly Detection Techniques and Applications (6 papers) and Domain Adaptation and Few-Shot Learning (5 papers). Jeonghong Kim collaborates with scholars based in South Korea, Singapore and Pakistan. Jeonghong Kim's co-authors include Bekhzod Olimov, Anand Paul, Anand Paul, Mohammed Maray, Kil-Houm Park, Sadia Din, Jae-Soo Kim, Sang‐Chul Kim, Kalyana C. Veluvolu and Abdul Rehman and has published in prestigious journals such as Scientific Reports, IEEE Access and Computers & Industrial Engineering.

In The Last Decade

Jeonghong Kim

24 papers receiving 399 citations

Peers

Jeonghong Kim

AI

CVPR

HI

CNC

IS

Yongfeng Dong China

Achmad Basuki Indonesia

Raihan Ul Islam Bangladesh

Hameedur Rahman Pakistan

Achin Jain India

M. Iyapparaja India

Iza Sazanita Isa Malaysia

Ioannis Rallis Greece

Bekhzod Olimov South Korea

Gabriel Sánchez-Pérez Mexico

Yongfeng Dong China

Jeonghong Kim

145 ×1.1

AI

226 ×2.0

CVPR

54 ×0.9

HI

31 ×0.6

CNC

34 ×0.7

IS

Citations per year, relative to Jeonghong Kim Jeonghong Kim (= 1×) peers Yongfeng Dong

Countries citing papers authored by Jeonghong Kim

Since Specialization

Citations

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

Fields of papers citing papers by Jeonghong Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeonghong Kim

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

All Works

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20 of 20 papers shown

1.

Kim, Jeonghong, et al.. (2025). Real-time isolation of physiological tremor using recursive singular spectrum analysis and random vector functional link for surgical robotics. ISA Transactions. 158. 556–571.

2.

Kim, Jeonghong, et al.. (2025). A hybrid unsupervised-weakly supervised method for video anomaly detection. Pattern Analysis and Applications. 28(3).

3.

Kim, Jeonghong, et al.. (2024). AONet: Attention network with optional activation for unsupervised video anomaly detection. ETRI Journal. 46(5). 890–903. 2 indexed citations

4.

Olimov, Bekhzod, et al.. (2023). Consecutive multiscale feature learning-based image classification model. Scientific Reports. 13(1). 3595–3595. 17 indexed citations

5.

Kim, Jeonghong, et al.. (2022). Digital Twin Model: A Real-Time Emotion Recognition System for Personalized Healthcare. IEEE Access. 10. 81155–81165. 46 indexed citations

6.

Olimov, Bekhzod, et al.. (2022). An integrated mediapipe-optimized GRU model for Indian sign language recognition. Scientific Reports. 12(1). 65 indexed citations

7.

Olimov, Bekhzod, Kalyana C. Veluvolu, Anand Paul, & Jeonghong Kim. (2022). UzADL: Anomaly detection and localization using graph Laplacian matrix-based unsupervised learning method. Computers & Industrial Engineering. 171. 108313–108313. 29 indexed citations

8.

Paul, Anand, et al.. (2022). Metrics Space and Norm: Taxonomy to Distance Metrics. Scientific Programming. 2022. 1–11. 1 indexed citations

9.

Olimov, Bekhzod, Seok‐Joo Koh, & Jeonghong Kim. (2021). AEDCN-Net: Accurate and Efficient Deep Convolutional Neural Network Model for Medical Image Segmentation. IEEE Access. 9. 154194–154203. 13 indexed citations

10.

Olimov, Bekhzod, et al.. (2021). FU-Net: fast biomedical image segmentation model based on bottleneck convolution layers. Multimedia Systems. 27(4). 637–650. 31 indexed citations

11.

Olimov, Bekhzod, Jeonghong Kim, & Anand Paul. (2021). REF-Net: Robust, Efficient, and Fast Network for Semantic Segmentation Applications Using Devices With Limited Computational Resources. IEEE Access. 9. 15084–15098. 17 indexed citations

12.

Paul, Anand, et al.. (2021). Predictive Modeling and Mobility Pattern Analysis. 1–4. 1 indexed citations

13.

Olimov, Bekhzod, et al.. (2020). Improved U-Net: Fully Convolutional Network Model for Skin-Lesion Segmentation. Applied Sciences. 10(10). 3658–3658. 26 indexed citations

14.

Olimov, Bekhzod & Jeonghong Kim. (2020). DeepCleanNet: Training Deep Convolutional Neural Network with Extremely Noisy Labels. Journal of Korea Multimedia Society. 23(11). 1349–1360. 2 indexed citations

15.

Olimov, Bekhzod, et al.. (2020). Missing Data Imputation for Geolocation-based Price Prediction Using KNN–MCF Method. ISPRS International Journal of Geo-Information. 9(4). 227–227. 35 indexed citations

16.

Olimov, Bekhzod, et al.. (2020). Weight initialization based‐rectified linear unit activation function to improve the performance of a convolutional neural network model. Concurrency and Computation Practice and Experience. 33(22). 35 indexed citations

17.

Rehman, Abdul, et al.. (2020). Weight Dropout for Preventing Neural Networks from Overfitting. 1–4. 15 indexed citations

18.

Kim, Jeonghong. (2018). Development of Visual Inspection System for Assembly Machine. 1 indexed citations

19.

Kim, Jeonghong, et al.. (2015). An Empirical Analysis of Characteristics and Job Creations in Technology-based Start-ups. 17(2). 167–193. 1 indexed citations

20.

Kim, Jae-Soo, Jeonghong Kim, & Dharma P. Agrawal. (2006). Broadcasting based on Selfish Probability in Mobile Ad Hoc Networks. 195–198. 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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