Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection S Kim, S Park, B Na, S Yoon AAAI, 2020 | 368* | 2020 |
Fast and efficient information transmission with burst spikes in deep spiking neural networks S Park, S Kim, H Choe, S Yoon Proceedings of the 56th Annual Design Automation Conference 2019, 53, 2019 | 117 | 2019 |
AutoSNN: towards energy-efficient spiking neural networks B Na, J Mok, S Park, D Lee, H Choe, S Yoon International Conference on Machine Learning, 16253-16269, 2022 | 51 | 2022 |
Near-Data Processing for Differentiable Machine Learning Models H Choe, S Lee, H Nam, S Park, S Kim, EY Chung, S Yoon MSST, 2017 | 28 | 2017 |
State-based full predication for low power coarse-grained reconfigurable architecture K Han, S Park, K Choi 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2012 | 28 | 2012 |
Quantized memory-augmented neural networks S Park, S Kim, S Lee, H Bae, S Yoon Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 24 | 2018 |
T2FSNN: deep spiking neural networks with time-to-first-spike coding S Park, S Kim, B Na, S Yoon 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 18* | 2020 |
Towards fast and accurate object detection in bio-inspired spiking neural networks through Bayesian optimization S Kim, S Park, B Na, J Kim, S Yoon IEEE Access, 2020 | 16* | 2020 |
Energy-Efficient Inference Accelerator for Memory-Augmented Neural Networks on an FPGA S Park, J Jang, S Kim, S Yoon 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2019 | 14* | 2019 |
An approach to code compression for CGRA S Park, K Choi 2011 3rd Asia symposium on quality electronic design (ASQED), 240-245, 2011 | 13 | 2011 |
Noise-Robust Deep Spiking Neural Networks with Temporal Information S Park, D Lee, S Yoon DAC, 2021 | 10 | 2021 |
Training Energy-Efficient Deep Spiking Neural Networks with Time-to-First-Spike Coding S Park, S Yoon arXiv preprint arXiv:2106.02568, 2021 | 8 | 2021 |
Memory-Augmented Neural Networks on FPGA for Real-Time and Energy-Efficient Question Answering S Park, J Jang, S Kim, B Na, S Yoon IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29 (1), 162-175, 2020 | 5 | 2020 |
Analysis of the training performance and time of SNN by STDP algorithms and spike temporal interactions S Park, S Yoon KIISE Trans. Comput. Practices 24 (9), 482-486, 2018 | 3 | 2018 |
CloudSocket: Fine-Grained Power Sensing System for Datacenters S Lee, H Kim, S Park, S Kim, H Choe, S Yoon IEEE Access 6, 49601-49610, 2018 | 3 | 2018 |
Scalable Smartphone Cluster for Deep Learning B Na, J Jang, S Park, S Kim, J Kim, MS Jeong, KC Kim, S Heo, Y Kim, ... arXiv preprint arXiv:2110.12172, 2021 | 2 | 2021 |
An Efficient Approach to Boosting Performance of Deep Spiking Network Training S Park, S Lee, H Nam, S Yoon NIPS 2016 Workshop on Computing with Spikes, 2016 | 2 | 2016 |
CloudSocket: Smart grid platform for datacenters S Lee, H Kim, S Park, S Kim, H Choe, CS Jeong, S Yoon 2016 IEEE 34th International Conference on Computer Design (ICCD), 436-439, 2016 | 2 | 2016 |
Hardware Implementation of Network Connectivity Relationships Using 2D hBN‐Based Artificial Neuron and Synaptic Devices Y Jo, DY Woo, G Noh, E Park, MJ Kim, YW Sung, DK Lee, J Park, J Kim, ... Advanced Functional Materials 34 (10), 2309058, 2024 | 1 | 2024 |
Reduction of carrier density and enhancement of the bulk Rashba spin-orbit coupling strength in Bi2Te3/GeTe superlattices SW Cho, YW Lee, SH Kim, S Han, I Kim, JK Park, JY Kwak, J Kim, ... Journal of Alloys and Compounds 957, 170444, 2023 | 1 | 2023 |