Young Im Cho

3.2k total citations
176 papers, 1.8k citations indexed

About

Young Im Cho is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Young Im Cho has authored 176 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Computer Vision and Pattern Recognition, 47 papers in Artificial Intelligence and 24 papers in Information Systems. Recurrent topics in Young Im Cho's work include Fire Detection and Safety Systems (21 papers), Video Surveillance and Tracking Methods (15 papers) and AI in cancer detection (12 papers). Young Im Cho is often cited by papers focused on Fire Detection and Safety Systems (21 papers), Video Surveillance and Tracking Methods (15 papers) and AI in cancer detection (12 papers). Young Im Cho collaborates with scholars based in South Korea, Uzbekistan and Egypt. Young Im Cho's co-authors include Akmalbek Abdusalomov, Shakhnoza Muksimova, Fazliddin Makhmudov, Mukhriddin Mukhiddinov, Sabina Umirzakova, Farkhod Akhmedov, Батырхан Омаров, Rashid Nasimov, Rashid Nasimov and Alpamis Kutlimuratov and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Young Im Cho

157 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Young Im Cho South Korea 24 663 472 346 193 142 176 1.8k
Akmalbek Abdusalomov South Korea 25 831 1.3× 595 1.3× 308 0.9× 139 0.7× 178 1.3× 77 1.7k
Ruimin Ke United States 25 593 0.9× 403 0.9× 428 1.2× 323 1.7× 194 1.4× 56 3.2k
Yanjie Duan China 9 373 0.6× 171 0.4× 603 1.7× 320 1.7× 102 0.7× 14 3.5k
Zhengbing He China 32 253 0.4× 573 1.2× 293 0.8× 375 1.9× 164 1.2× 125 4.6k
Pan Lu United States 23 375 0.6× 505 1.1× 471 1.4× 126 0.7× 65 0.5× 119 2.1k
Hao Xue China 17 351 0.5× 158 0.3× 334 1.0× 131 0.7× 69 0.5× 86 1.2k
Huaiyu Wan China 20 324 0.5× 168 0.4× 926 2.7× 270 1.4× 110 0.8× 72 4.4k
Hao Wang China 33 192 0.3× 716 1.5× 150 0.4× 442 2.3× 105 0.7× 302 3.9k
Kapil Sharma India 24 369 0.6× 138 0.3× 430 1.2× 308 1.6× 46 0.3× 165 1.8k
Weili Fang Australia 26 335 0.5× 233 0.5× 544 1.6× 78 0.4× 78 0.5× 45 3.1k

Countries citing papers authored by Young Im Cho

Since Specialization
Citations

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

Fields of papers citing papers by Young Im Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young Im Cho. 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 Young Im Cho. The network helps show where Young Im Cho may publish in the future.

Co-authorship network of co-authors of Young Im Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Young Im Cho. A scholar is included among the top collaborators of Young Im Cho 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 Young Im Cho. Young Im Cho 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.
Muksimova, Shakhnoza, et al.. (2025). A lightweight attention-driven YOLOv5m model for improved brain tumor detection. Computers in Biology and Medicine. 188. 109893–109893. 6 indexed citations
2.
Umirzakova, Sabina, et al.. (2025). Iterative contextual and adaptive strategies for enhanced monocular depth estimation. Engineering Applications of Artificial Intelligence. 160. 111898–111898.
3.
Muksimova, Shakhnoza, et al.. (2025). Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI. Computers in Biology and Medicine. 190. 110095–110095. 6 indexed citations
4.
Muksimova, Shakhnoza, et al.. (2025). Cross-Modal Transformer-Based Streaming Dense Video Captioning with Neural ODE Temporal Localization. Sensors. 25(3). 707–707. 5 indexed citations
5.
Abdusalomov, Akmalbek, et al.. (2025). Hybrid Cloud-Based Information and Control System Using LSTM-DNN Neural Networks for Optimization of Metallurgical Production. Processes. 13(7). 2237–2237. 1 indexed citations
6.
Cho, Young Im, et al.. (2025). Accelerating Deep Learning-Based Morphological Biometric Recognition with Field-Programmable Gate Arrays. AI. 6(1). 8–8. 1 indexed citations
7.
Muksimova, Shakhnoza, et al.. (2024). Novelty Classification Model Use in Reinforcement Learning for Cervical Cancer. Cancers. 16(22). 3782–3782. 13 indexed citations
8.
Nasimov, Rashid, et al.. (2024). GAN-Based Novel Approach for Generating Synthetic Medical Tabular Data. Bioengineering. 11(12). 1288–1288. 2 indexed citations
9.
Cho, Young Im, et al.. (2024). Securing Online Job Platforms: A Distributed Framework for Combating Employment Fraud in the Digital Landscape. International Journal of Safety and Security Engineering. 14(6). 1647–1665.
10.
Nasimov, Rashid, et al.. (2024). Effective Methods of Categorical Data Encoding for Artificial Intelligence Algorithms. Mathematics. 12(16). 2553–2553. 14 indexed citations
11.
Jaleel, Abdul, Naeem Iqbal, Anwar Ghani, et al.. (2024). Hybrid Approach to Automated Essay Scoring: Integrating Deep Learning Embeddings with Handcrafted Linguistic Features for Improved Accuracy. Mathematics. 12(21). 3416–3416. 6 indexed citations
12.
Cho, Young Im, et al.. (2024). An application for solving minimization problems using the Harmony search algorithm. SoftwareX. 27. 101783–101783. 1 indexed citations
13.
14.
Cho, Young Im, et al.. (2024). GAN-Based High-Quality Face-Swapping Composite Network. Electronics. 13(15). 3092–3092. 2 indexed citations
15.
Cho, Young Im, et al.. (2024). Automated Multi-Class Facial Syndrome Classification Using Transfer Learning Techniques. Bioengineering. 11(8). 827–827. 2 indexed citations
16.
Elnemr, Heba A., et al.. (2023). User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions. Sensors. 23(3). 1521–1521. 2 indexed citations
17.
Aslan, Heba K., et al.. (2023). Lightweight Computational Complexity Stepping Up the NTRU Post-Quantum Algorithm Using Parallel Computing. Symmetry. 16(1). 12–12. 2 indexed citations
18.
Cho, Young Im, et al.. (2022). MediaPipe’s Landmarks with RNN for Dynamic Sign Language Recognition. Electronics. 11(19). 3228–3228. 36 indexed citations
19.
Makhmudov, Fazliddin, et al.. (2022). Modeling Speech Emotion Recognition via Attention-Oriented Parallel CNN Encoders. Electronics. 11(23). 4047–4047. 20 indexed citations
20.
Cho, Young Im, et al.. (2020). Automatic Metallic Surface Defect Detection using ShuffleDefectNet. Journal of the Korea Society of Computer and Information. 25(3). 19–26. 10 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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