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Dahun Choi
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2020 – today
- 2024
- [j1]Hyeonseok Hong, Dahun Choi, Namjoon Kim, Haein Lee, Beom Jin Kang, Huibeom Kang, Hyun Kim:
Survey of convolutional neural network accelerators on field-programmable gate array platforms: architectures and optimization techniques. J. Real Time Image Process. 21(3): 64 (2024) - [c6]Sangbeom Jeong, Dahun Choi, Hyun Kim:
SRU-Q: Hardware-friendly Stochastic Rounding Unit-based Gradient Quantization for CNN Training. AICAS 2024: 457-461 - [c5]Dahun Choi, Hyun Kim:
GDS: Gradient Distribution Scaling-based Gradient Quantization for Low-complexity and Hardware-friendly Training of Instance Segmentation Models. ICEIC 2024: 1-2 - [c4]Beom Jin Kang, Dahun Choi, Hyun Kim:
Mixed Precision Quantization with Hardware-Friendly Activation Functions for Hybrid ViT Models. ICEIC 2024: 1-2 - [c3]Dahun Choi, Hyun Kim:
ARC: Adaptive Rounding and Clipping Considering Gradient Distribution for Deep Convolutional Neural Network Training. ISCAS 2024: 1-5 - 2022
- [c2]Dahun Choi, Hyun Kim:
Hardware-Friendly Logarithmic Quantization with Mixed-Precision for MobileNetV2. AICAS 2022: 348-351 - 2021
- [c1]Dahun Choi, Hyun Kim:
Hardware-friendly Log-scale Quantization for CNNs with Activation Functions Containing Negative Values. ISOCC 2021: 415-416
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last updated on 2024-08-01 21:09 CEST by the dblp team
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