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Dongjoo Shin
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2020 – today
- 2022
- [j11]Dongjoo Shin, Hyeong-U. Kim
, Atul Kulkarni
Development of Force Sensor System Based on Tri-Axial Fiber Bragg Grating with Flexure Structure. Sensors 22(1): 16 (2022) - [c25]Hyunho Seok, Dongjoo Shin, Hyeong-U. Kim, Taesung Kim:
Flexible Sensor Platform: Nano-grain of 2D Heterostructure by Cold-Plasma. MeMeA 2022: 1-6 - [c24]Dongjoo Shin, Jin-Hyoung Lee, Taesung Kim, Hyunho Seok:
Flexible and Stretchable Optical Fiber Strain Sensor based on Nanoparticles and Polymer for Human Motion Detection. MeMeA 2022: 1-5 - 2021
- [c23]Dongjoo Shin, Taesung Kim:
Wearable Sensor based on Fiber Bragg Grating with Flexible Polymer for Squat Exercise. MetroInd4.0&IoT 2021: 478-481 - 2020
- [j10]Dongjoo Shin
The Heterogeneous Deep Neural Network Processor With a Non-von Neumann Architecture. Proc. IEEE 108(8): 1245-1260 (2020) - [j9]Jinsu Lee
The Hardware and Algorithm Co-Design for Energy-Efficient DNN Processor on Edge/Mobile Devices. IEEE Trans. Circuits Syst. 67-I(10): 3458-3470 (2020) - [c22]Paolo Resta, Daniela Lo Presti, Emiliano Schena, Carlo Massaroni, Domenico Formica, Taesung Kim, Dongjoo Shin:
A wearable system for knee flexion/extension monitoring: design and assessment. MetroInd4.0&IoT 2020: 273-277
2010 – 2019
- 2019
- [j8]Jinmook Lee
UNPU: An Energy-Efficient Deep Neural Network Accelerator With Fully Variable Weight Bit Precision. IEEE J. Solid State Circuits 54(1): 173-185 (2019) - [c21]Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sungpill Choi, Youngwoo Kim, Hoi-Jun Yoo:
A 2.1TFLOPS/W Mobile Deep RL Accelerator with Transposable PE Array and Experience Compression. ISSCC 2019: 136-138 - [c20]Dongjoo Shin, Hyeong-U. Kim, Taesung Kim:
Development and Evaluation of Tri-Axial Fiber Bragg Grating in a Measurement Module for Catheterization. MetroInd4.0&IoT 2019: 158-161 - [c19]Juhyoung Lee, Dongjoo Shin, Jinsu Lee, Jinmook Lee, Sanghoon Kang, Hoi-Jun Yoo:
A Full HD 60 fps CNN Super Resolution Processor with Selective Caching based Layer Fusion for Mobile Devices. VLSI Circuits 2019: 302- - 2018
- [j7]Dongjoo Shin, Jinmook Lee, Jinsu Lee, Juhyoung Lee, Hoi-Jun Yoo:
DNPU: An Energy-Efficient Deep-Learning Processor with Heterogeneous Multi-Core Architecture. IEEE Micro 38(5): 85-93 (2018) - [j6]Youchang Kim
A 0.55 V 1.1 mW Artificial Intelligence Processor With On-Chip PVT Compensation for Autonomous Mobile Robots. IEEE Trans. Circuits Syst. I Regul. Pap. 65-I(2): 567-580 (2018) - [c18]Juhyoung Lee, Changhyeon Kim, Sungpill Choi, Dongjoo Shin, Sanghoon Kang, Hoi-Jun Yoo:
A 46.1 fps Global Matching Optical Flow Estimation Processor for Action Recognition in Mobile Devices. ISCAS 2018: 1-5 - [c17]Jinmook Lee, Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sangyeob Kim, Hoi-Jun Yoo:
UNPU: A 50.6TOPS/W unified deep neural network accelerator with 1b-to-16b fully-variable weight bit-precision. ISSCC 2018: 218-220 - [c16]Dongjoo Shin, Taesung Kim, Hyeong-U. Kim:
Development of Tri-axial Fiber Bragg Grating Force Sensor in Catheter Application. MeMeA 2018: 1-5 - 2017
- [j5]Youchang Kim, Dongjoo Shin, Jinsu Lee, Hoi-Jun Yoo:
BRAIN: A Low-Power Deep Search Engine for Autonomous Robots. IEEE Micro 37(5): 11-19 (2017) - [j4]Jinsu Lee
A 17.5-fJ/bit Energy-Efficient Analog SRAM for Mixed-Signal Processing. IEEE Trans. Very Large Scale Integr. Syst. 25(10): 2714-2723 (2017) - [c15]Jinmook Lee, Dongjoo Shin, Hoi-Jun Yoo:
A 21mW low-power recurrent neural network accelerator with quantization tables for embedded deep learning applications. A-SSCC 2017: 237-240 - [c14]Dongjoo Shin, Jinmook Lee, Jinsu Lee, Juhyoung Lee, Hoi-Jun Yoo:
An energy-efficient deep learning processor with heterogeneous multi-core architecture for convolutional neural networks and recurrent neural networks. COOL Chips 2017: 1-2 - [c13]Dongjoo Shin, Jinmook Lee, Jinsu Lee, Hoi-Jun Yoo:
14.2 DNPU: An 8.1TOPS/W reconfigurable CNN-RNN processor for general-purpose deep neural networks. ISSCC 2017: 240-241 - [c12]Dongjoo Shin, Youchang Kim, Hoi-Jun Yoo:
A 1.41mW on-chip/off-chip hybrid transposition table for low-power robust deep tree search in artificial intelligence SoCs. SoCC 2017: 138-142 - 2016
- [j3]Injoon Hong, Kyeongryeol Bong, Dongjoo Shin, Seongwook Park, Kyuho Jason Lee
A 2.71 nJ/Pixel Gaze-Activated Object Recognition System for Low-Power Mobile Smart Glasses. IEEE J. Solid State Circuits 51(1): 45-55 (2016) - [c11]Youchang Kim
A 1.1 mW 32-thread artificial intelligence processor with 3-level transposition table and on-chip PVT compensation for autonomous mobile robots. COOL Chips 2016: 1-2 - [c10]Jinsu Lee, Dongjoo Shin, Youchang Kim
A 17.5 fJ/bit energy-efficient analog SRAM for mixed-signal processing. ISCAS 2016: 1010-1013 - [c9]Youchang Kim
14.3 A 0.55V 1.1mW artificial-intelligence processor with PVT compensation for micro robots. ISSCC 2016: 258-259 - 2015
- [j2]Seongwook Park, Junyoung Park, Kyeongryeol Bong, Dongjoo Shin, Jinmook Lee, Sungpill Choi, Hoi-Jun Yoo:
An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications. IEEE Trans. Biomed. Circuits Syst. 9(6): 838-848 (2015) - [c8]Injoon Hong, Dongjoo Shin, Youchang Kim
A keypoint-level parallel pipelined object recognition processor with gaze activation image sensor for mobile smart glasses system. COOL Chips 2015: 1-3 - [c7]Injoon Hong, Kyeongryeol Bong, Dongjoo Shin, Seongwook Park, Kyuho Jason Lee
18.1 A 2.71nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile HMD applications. ISSCC 2015: 1-3 - [c6]Seongwook Park, Kyeongryeol Bong, Dongjoo Shin, Jinmook Lee, Sungpill Choi, Hoi-Jun Yoo:
4.6 A1.93TOPS/W scalable deep learning/inference processor with tetra-parallel MIMD architecture for big-data applications. ISSCC 2015: 1-3 - [c5]Dongjoo Shin, Injoon Hong, Gyeonghoon Kim, Hoi-Jun Yoo:
A 33 nJ/vector descriptor generation processor for low-power object recognition. VLSIC 2015: 52- - 2014
- [j1]Taehwan Roh, Kiseok Song, Hyunwoo Cho, Dongjoo Shin, Hoi-Jun Yoo:
A Wearable Neuro-Feedback System With EEG-Based Mental Status Monitoring and Transcranial Electrical Stimulation. IEEE Trans. Biomed. Circuits Syst. 8(6): 755-764 (2014) - [c4]Gyeonghoon Kim, Seongwook Park, Kyuho Jason Lee
A task-level pipelined many-SIMD augmented reality processor with congestion-aware network-on-chip scheduler. COOL Chips 2014: 1-3 - [c3]Dongjoo Shin, Injoon Hong, Hoi-Jun Yoo:
An 1.92mW Feature Reuse Engine based on inter-frame similarity for low-power object recognition in video frames. ISCAS 2014: 758-761 - [c2]Gyeonghoon Kim, Youchang Kim
10.4 A 1.22TOPS and 1.52mW/MHz augmented reality multi-core processor with neural network NoC for HMD applications. ISSCC 2014: 182-183 - [c1]Taehwan Roh, Kiseok Song, Hyunwoo Cho, Dongjoo Shin, Unsoo Ha, Kwonjoon Lee, Hoi-Jun Yoo:
18.5 A 2.14mW EEG neuro-feedback processor with transcranial electrical stimulation for mental-health management. ISSCC 2014: 318-319
Coauthor Index
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