| Fire in your hands: Understanding thermal behavior of smartphones S Kang, H Choi, S Park, C Park, J Lee, U Lee, SJ Lee The 25th Annual International Conference on Mobile Computing and Networking …, 2019 | 52 | 2019 |
| Smart phone power model generation using use pattern analysis J Lee, H Joe, H Kim 2012 IEEE International Conference on Consumer Electronics (ICCE), 412-413, 2012 | 31 | 2012 |
| Quantune: Post-training quantization of convolutional neural networks using extreme gradient boosting for fast deployment J Lee, M Yu, Y Kwon, T Kim Future Generation Computer Systems 132, 124-135, 2022 | 20 | 2022 |
| Reducing distraction of smartwatch users with deep learning J Lee, J Kwon, H Kim Proceedings of the 18th International Conference on Human-Computer …, 2016 | 18 | 2016 |
| Automated power model generation method for smartphones J Lee, H Joe, H Kim IEEE Transactions on Consumer Electronics 60 (2), 190-197, 2014 | 17 | 2014 |
| PASS: Reducing Redundant Notifications between a Smartphone and a Smartwatch for Energy Saving J Lee, U Lee, H Kim IEEE Transactions on Mobile Computing, 2020 | 12 | 2020 |
| Hardware resource analysis in distributed training with edge devices S Park, J Lee, H Kim Electronics 9 (1), 28, 2019 | 9 | 2019 |
| 스마트폰 응용 프로그램의 소모전력 분석 이제민， 조현우， 김형신 한국정보과학회 학술발표논문집 38 (2D), 39-42, 2011 | 9 | 2011 |
| Q-HyViT: Post-Training Quantization of Hybrid Vision Transformers With Bridge Block Reconstruction for IoT Systems J Lee, Y Kwon, S Park, M Yu, J Park, H Song IEEE Internet of Things Journal, 2024 | 8* | 2024 |
| QDroid: Mobile application quality analyzer for app market curators J Lee, H Kim Mobile Information Systems 2016 (1), 1740129, 2016 | 7 | 2016 |
| CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution T Kim, Y Kwon, J Lee, S Ha ECCV, 2022 | 6 | 2022 |
| Framework for automated power estimation of android applications J Lee, H Kim Proceeding of the 11th annual international conference on Mobile systems …, 2013 | 5 | 2013 |
| Pipelining of a Mobile SoC and an External NPU for Accelerating CNN Inference J Kwon, J Lee, H Kim IEEE Embedded Systems Letters, 2023 | 4 | 2023 |
| Understanding Customers' Interests in the Wild S Kang, A Kim, J Lee, I Shin, U Lee Proceedings of the 2018 ACM International Joint Conference and 2018 …, 2018 | 4 | 2018 |
| Reducing smartwatch users’ distraction with convolutional neural network J Lee, J Kwon, H Kim Mobile Information Systems 2018 (1), 7689549, 2018 | 4 | 2018 |
| Output-oriented power saving mode for mobile devices H Joe, J Kim, J Lee, H Kim Future Generation Computer Systems 72, 49-64, 2017 | 3 | 2017 |
| 스마트폰 응용프로그램 에너지 소모 분석을 위한 프레임워크 이제민， 조현우， 김형신 정보과학회논문지: 컴퓨팅의 실제 및 레터 18 (11), 780-784, 2012 | 2 | 2012 |
| NEST‐C: A deep learning compiler framework for heterogeneous computing systems with artificial intelligence accelerators J Park, M Yu, J Kwon, J Park, J Lee, Y Kwon ETRI Journal 46 (5), 851-864, 2024 | 1 | 2024 |
| A comprehensive evaluation of quantized instruction-tuned large language models: An experimental analysis up to 405b J Lee, S Park, J Kwon, J Oh, Y Kwon arXiv preprint arXiv:2409.11055, 2024 | 1 | 2024 |
| ACLTuner: A Profiling-Driven Fast Tuning to Optimized Deep Learning Inference Y Kwon, JH Cha, J Lee, M Yu, J Park, J Lee Machine Learning for Systems Workshops at 37th NeurIPS 2023, 2023 | 1 | 2023 |
hyungshin kimChungnam national universityEmail verificata su cnu.ac.kr