Changhyeon Kim

34 papers receiving 1.1k citations

Peers

Changhyeon Kim
Comparison fields: 5 of 82
  • Electrical and Electronic Engineering 674
  • Computer Vision and Pattern Recognition 485
  • Artificial Intelligence 225
  • Biomaterials 125
  • Biomedical Engineering 119
Replace Parviz Keshavarzi with:
Parviz Keshavarzi Iran
Xing Hu China
Bashir I. Morshed United States
Chang Gao China
Wen Zhou China
Andy Zhou United States
Tianhang Zheng China
Tony F. Wu United States
Hazem M. Abbas Egypt
Xiongwei Zhang China
Changhyeon Kim relative to Parviz Keshavarzi Iran Parviz Keshavarzi's profile →
Citations per field
00.5×3.3×
Parviz Keshavarzi · 1×
Citations per year

Countries citing papers authored by Changhyeon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Changhyeon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changhyeon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Changhyeon Kim. A scholar is included among the top collaborators of Changhyeon 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 Changhyeon Kim. Changhyeon Kim 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
#WorkIndexed citations
1 0
2 1
3 16
4 11
5 24
6 46
7 232
8 236
9
UNPU: A 50.6TOPS/W Energy-Efficient Unified Deep Neural-Network Accelerator with 1-to-16b Fully Variable Bit Precision UNPU: A 50.6TOPS/W Energy-Efficient Unified Deep Neural-Network Accelerator with 1-to-16b Fully Variable Bit Precision
1
10 106
11 24
12
A 0.62mW Ultra-low-power Convolutional Neural Network Face Recognition Processor and a CIS Integrated with Always-on Haar-like Face Detector
8
13 84
14
A 502GOPS and 0.984mW Dual-Mode ADAS SoC with RNN-FIS Engine for Intention Prediction in Automotive Black-Box System
13
15 22
16 2
17
A Wearable EEG-HEG-HRV Multimodal System with Real-time Transcranial Electrical Stimulation Monitoring for Mental Health Management
3
18 4
19 11
20 8

About Changhyeon Kim

Changhyeon Kim is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Hardware and Architecture, having authored 36 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (10 papers), CCD and CMOS Imaging Sensors (9 papers) and Face and Expression Recognition (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (485 citations), Hardware and Architecture (91 citations) and Electrical and Electronic Engineering (674 citations). Changhyeon Kim has collaborated with scholars based in South Korea and Belgium. Frequent co-authors include Hoi‐Jun Yoo, Sanghoon Kang, Dongjoo Shin, Jinmook Lee, Sangyeob Kim, Kyeongryeol Bong, Sungpill Choi, Kuk Young Cho, Jung‐Ki Park and Donghyeon Han. Their work appears in journals such as IEEE Journal of Solid-State Circuits, Journal of Applied Polymer Science and Polymer Engineering and Science.

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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