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Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection
S Kim, S Park, B Na, S Yoon
AAAI, 2020
346*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
1122019
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
462022
Near-Data Processing for Differentiable Machine Learning Models
H Choe, S Lee, H Nam, S Park, S Kim, EY Chung, S Yoon
MSST, 2017
282017
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
282012
Quantized memory-augmented neural networks
S Park, S Kim, S Lee, H Bae, S Yoon
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
232018
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
17*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
132011
Noise-Robust Deep Spiking Neural Networks with Temporal Information
S Park, D Lee, S Yoon
DAC, 2021
92021
Training Energy-Efficient Deep Spiking Neural Networks with Time-to-First-Spike Coding
S Park, S Yoon
arXiv preprint arXiv:2106.02568, 2021
82021
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
52020
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
32018
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
32018
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
22021
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
22016
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
22016
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
12023
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, 2309058, 2023
12023
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