Jinmook Lee

1.7k citations

25 papers · 1.2k indexed · h-index 15

Impact in

Computer Vision and Pattern Recognition top 1%
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
Computational Mathematics top 10%

Papers in

Computer Vision and Pattern Recognition 17
- Advanced Neural Network Applications 12
- Advanced Image and Video Retrieval Techniques 4
- Face and Expression Recognition 3
Signal Processing 5
- Speech and Audio Processing 5

Co-authors: Hoi‐Jun Yoo Dongjoo Shin Jinsu Lee Sanghoon Kang Changhyeon Kim Sangyeob Kim Donghyeon Han Juhyoung Lee
Journals: IEEE Transactions on Circuits and Systems I Regular Papers (3 papers)IEEE Solid-State Circuits Letters (2 papers)IEEE Transactions on Circuits & Systems II Express Briefs (1 paper)IEEE Journal on Emerging and Selected Topics in Circuits and Systems (1 paper)IEEE Journal of Solid-State Circuits (1 paper)
Partner nations: South Korea

In The Last Decade

Jinmook Lee

25 papers receiving 1.2k citations

Peers

Countries citing papers authored by Jinmook Lee

Since Specialization

Citations

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

Fields of papers citing papers by Jinmook Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Jinmook Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jinmook Lee Line = papers co-authored together Jinmook Lee links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	The Hardware and Algorithm Co-Design for Energy-Efficient DNN Processor on Edge/Mobile Devices IEEE Transactions on Circuits and Systems I Regular Papers ·Jinsu Lee, Sanghoon Kang, Jinmook Lee, Dongjoo Shin, Donghyeon Han, Hoi‐Jun Yoo	2020	36
2	PNPU: An Energy-Efficient Deep-Neural-Network Learning Processor With Stochastic Coarse–Fine Level Weight Pruning and Adaptive Input/Output/Weight Zero Skipping IEEE Solid-State Circuits Letters ·Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinmook Lee, H. Yamaguchi, Hoi‐Jun Yoo	2020	12
3	A 146.52 TOPS/W Deep-Neural-Network Learning Processor with Stochastic Coarse-Fine Pruning and Adaptive Input/Output/Weight Skipping Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinmook Lee, Hoi‐Jun Yoo	2020	24
4	The Development of Silicon for AI: Different Design Approaches IEEE Transactions on Circuits and Systems I Regular Papers ·Kyuho Lee, Jinmook Lee, Sungpill Choi, Hoi‐Jun Yoo	2020	13
5	An Energy-Efficient Sparse Deep-Neural-Network Learning Accelerator With Fine-Grained Mixed Precision of FP8–FP16 IEEE Solid-State Circuits Letters ·Jinsu Lee, Juhyoung Lee, Donghyeon Han, Jinmook Lee, Gwangtae Park, Hoi‐Jun Yoo	2019	19
6	A 1.32 TOPS/W Energy Efficient Deep Neural Network Learning Processor with Direct Feedback Alignment based Heterogeneous Core Architecture Donghyeon Han, Jinsu Lee, Jinmook Lee, Hoi‐Jun Yoo	2019	25
7	A Full HD 60 fps CNN Super Resolution Processor with Selective Caching based Layer Fusion for Mobile Devices Juhyoung Lee, Dongjoo Shin, Jinsu Lee, Jinmook Lee, Sanghoon Kang, Hoi‐Jun Yoo	2019	29
8	7.7 LNPU: A 25.3TFLOPS/W Sparse Deep-Neural-Network Learning Processor with Fine-Grained Mixed Precision of FP8-FP16 Jinsu Lee, Juhyoung Lee, Donghyeon Han, Jinmook Lee, Gwangtae Park, Hoi‐Jun Yoo	2019	114
9	UNPU: A 50.6TOPS/W unified deep neural network accelerator with 1b-to-16b fully-variable weight bit-precision Jinmook Lee, Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sangyeob Kim, Hoi‐Jun Yoo	2018	232
10	A Low-Power Deep Neural Network Online Learning Processor for Real-Time Object Tracking Application IEEE Transactions on Circuits and Systems I Regular Papers ·Donghyeon Han, Jinsu Lee, Jinmook Lee, Hoi‐Jun Yoo	2018	32
11	UNPU: An Energy-Efficient Deep Neural Network Accelerator With Fully Variable Weight Bit Precision IEEE Journal of Solid-State Circuits ·Jinmook Lee, Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sangyeob Kim, Hoi‐Jun Yoo	2018	236
12	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 Jinmook Lee, Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sangyeob Kim, Hoi‐Jun Yoo	2018	1
13	14.2 DNPU: An 8.1TOPS/W reconfigurable CNN-RNN processor for general-purpose deep neural networks Dongjoo Shin, Jinmook Lee, Jinsu Lee, Hoi‐Jun Yoo	2017	239
14	An energy-efficient deep learning processor with heterogeneous multi-core architecture for convolutional neural networks and recurrent neural networks Dongjoo Shin, Jinmook Lee, Jinsu Lee, Juhyoung Lee, Hoi‐Jun Yoo	2017	5
15	An 8.3mW 1.6Msamples/s multi-modal event-driven speech enhancement processor for robust speech recognition in smart glasses Jinmook Lee, Seong‐Wook Park, Injoon Hong, Hoi‐Jun Yoo	2016	2
16	An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications IEEE Transactions on Biomedical Circuits and Systems ·Seong‐Wook Park, Jun-Young Park, Kyeongryeol Bong, Dongjoo Shin, Jinmook Lee, Sungpill Choi, Hoi‐Jun Yoo	2016	34
17	14.1 A 126.1mW real-time natural UI/UX processor with embedded deep-learning core for low-power smart glasses Seong‐Wook Park, Sungpill Choi, Jinmook Lee, Zeqing Zhang, Jun-Young Park, Hoi‐Jun Yoo	2016	22
18	A 1.93 TOPS/W Scalable Deep Learning/Inference Processor with Tetra-parallel MIMD Architecture for Big Data Applications Hoi‐Jun Yoo, Seong‐Wook Park, Kyeongryeol Bong, Dongjoo Shin, Jinmook Lee, Sungpill Choi	2015	34
19	4.6 A1.93TOPS/W scalable deep learning/inference processor with tetra-parallel MIMD architecture for big-data applications Seong‐Wook Park, Kyeongryeol Bong, Dongjoo Shin, Jinmook Lee, Sungpill Choi, Hoi‐Jun Yoo	2015	78
20	A 3.13nJ/sample energy-efficient speech extraction processor for robust speech recognition in mobile head-mounted display systems Jinmook Lee, Seong‐Wook Park, Injoon Hong, Hoi‐Jun Yoo	2015	3

About Jinmook Lee

Jinmook Lee is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Media Technology, Electrical and Electronic Engineering and Computational Mechanics, having authored 25 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (12 papers), Advanced Memory and Neural Computing (9 papers), CCD and CMOS Imaging Sensors (6 papers), Speech and Audio Processing (5 papers), Ferroelectric and Negative Capacitance Devices (5 papers), Advanced Image and Video Retrieval Techniques (4 papers), Advanced Adaptive Filtering Techniques (3 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (711 citations), Computational Mathematics (14 citations), Hardware and Architecture (146 citations), Electrical and Electronic Engineering (830 citations) and Artificial Intelligence (383 citations). Jinmook Lee has collaborated with scholars based in South Korea. Frequent co-authors include Hoi‐Jun Yoo, Dongjoo Shin, Jinsu Lee, Sanghoon Kang, Changhyeon Kim, Sangyeob Kim, Donghyeon Han, Juhyoung Lee, Seong‐Wook Park and Sungpill Choi. Their work appears in journals such as IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Solid-State Circuits Letters, IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Journal on Emerging and Selected Topics in Circuits and Systems and IEEE Journal of Solid-State Circuits.

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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