Jae-Seok Choi

2.5k total citations
12 papers, 343 citations indexed

About

Jae-Seok Choi is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Networks and Communications. According to data from OpenAlex, Jae-Seok Choi has authored 12 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 6 papers in Media Technology and 1 paper in Computer Networks and Communications. Recurrent topics in Jae-Seok Choi's work include Advanced Image Processing Techniques (11 papers), Advanced Vision and Imaging (7 papers) and Image and Signal Denoising Methods (4 papers). Jae-Seok Choi is often cited by papers focused on Advanced Image Processing Techniques (11 papers), Advanced Vision and Imaging (7 papers) and Image and Signal Denoising Methods (4 papers). Jae-Seok Choi collaborates with scholars based in South Korea and United States. Jae-Seok Choi's co-authors include Munchurl Kim, Yongwoo Kim, Soomin Seo, Jaeheon Jeong, Doochun Seo, Hyeonjun Sim, Soo Ye Kim, Saehun Kim, Sung‐Ho Bae and Sehwan Ki and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Access and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Jae-Seok Choi

12 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jae-Seok Choi South Korea	9	307	184	21	15	13	12	343
Seo-Won Ji South Korea	6	447 1.5×	221 1.2×	24 1.1×	7 0.5×	16 1.2×	12	502
Domonkos Varga Hungary	12	358 1.2×	155 0.8×	19 0.9×	20 1.3×	27 2.1×	37	416
Zhaorong Li China	5	499 1.6×	292 1.6×	22 1.0×	8 0.5×	13 1.0×	24	565
Xiaoran Jiang France	9	362 1.2×	77 0.4×	26 1.2×	25 1.7×	28 2.2×	16	420
Meiqin Liu China	9	282 0.9×	85 0.5×	7 0.3×	30 2.0×	14 1.1×	39	318
Vorapoj Patanavijit Thailand	9	300 1.0×	154 0.8×	21 1.0×	23 1.5×	11 0.8×	108	349
Xin Luan China	7	255 0.8×	107 0.6×	8 0.4×	9 0.6×	11 0.8×	36	311
Dũng Trung Võ United States	7	418 1.4×	163 0.9×	11 0.5×	64 4.3×	5 0.4×	29	449
Yuting Tang China	5	390 1.3×	269 1.5×	15 0.7×	13 0.9×	20 1.5×	16	449

Countries citing papers authored by Jae-Seok Choi

Since Specialization

Citations

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

Fields of papers citing papers by Jae-Seok Choi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jae-Seok Choi

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

All Works

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12 of 12 papers shown

Choi, Jae-Seok, et al.. (2021). Faster Stochastic Block Partition Using Aggressive Initial Merging, Compressed Representation, and Parallelism Control. 1–7. 6 indexed citations

Seo, Soomin, et al.. (2020). UPSNet: Unsupervised Pan-Sharpening Network With Registration Learning Between Panchromatic and Multi-Spectral Images. IEEE Access. 8. 201199–201217. 32 indexed citations

Choi, Jae-Seok, Yongwoo Kim, & Munchurl Kim. (2019). S3: A Spectral-Spatial Structure Loss for Pan-Sharpening Networks. IEEE Geoscience and Remote Sensing Letters. 17(5). 829–833. 15 indexed citations

Ki, Sehwan, Hyeonjun Sim, Jae-Seok Choi, et al.. (2018). Fully End-to-End Learning Based Conditional Boundary Equilibrium GAN with Receptive Field Sizes Enlarged for Single Ultra-High Resolution Image Dehazing. 930–9307. 14 indexed citations

Sim, Hyeonjun, Sehwan Ki, Jae-Seok Choi, et al.. (2018). High-Resolution Image Dehazing with Respect to Training Losses and Receptive Field Sizes. 1025–10257. 16 indexed citations

Kim, Yongwoo, Jae-Seok Choi, & Munchurl Kim. (2018). 2X Super-Resolution Hardware Using Edge-Orientation-Based Linear Mapping for Real-Time 4K UHD 60 fps Video Applications. IEEE Transactions on Circuits & Systems II Express Briefs. 65(9). 1274–1278. 17 indexed citations

Kim, Yongwoo, Jae-Seok Choi, & Munchurl Kim. (2018). A Real-Time Convolutional Neural Network for Super-Resolution on FPGA With Applications to 4K UHD 60 fps Video Services. IEEE Transactions on Circuits and Systems for Video Technology. 29(8). 2521–2534. 73 indexed citations

Choi, Jae-Seok & Munchurl Kim. (2017). Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings. IEEE Transactions on Image Processing. 26(3). 1300–1314. 37 indexed citations

Choi, Jae-Seok & Munchurl Kim. (2017). A Deep Convolutional Neural Network with Selection Units for Super-Resolution. 1150–1156. 93 indexed citations

10.

Choi, Jae-Seok, Sung‐Ho Bae, & Munchurl Kim. (2015). A no-reference perceptual blurriness metric based fast super-resolution of still pictures using sparse representation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9401. 94010N–94010N. 6 indexed citations

11.

Choi, Jae-Seok, Sung‐Ho Bae, & Munchurl Kim. (2015). Single image super-resolution based on self-examples using context-dependent subpatches. 2835–2839. 6 indexed citations

12.

Choi, Jae-Seok & Munchurl Kim. (2015). Super-Interpolation With Edge-Orientation-Based Mapping Kernels for Low Complex Upscaling. IEEE Transactions on Image Processing. 25(1). 469–483. 28 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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