Dahun Choi

According to our database, Dahun Choi authored at least 11 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2025

Closit: Clipped-Regime Posit Quantization for Edge-Friendly Vision Transformers.

Sungsoo Han, Dahun Choi, Hyun Kim

Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems, 2025

GradQ-ViT: Robust and Efficient Gradient Quantization for Vision Transformers.

Dahun Choi, Hyun Kim

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Mobile-X: Dedicated FPGA Implementation of the MobileNet Accelerator Optimizing Depthwise Separable Convolution.

Hyeonseok Hong, Dahun Choi, Namjoon Kim, Hyun Kim

IEEE Trans. Circuits Syst. II Express Briefs, November, 2024

Survey of convolutional neural network accelerators on field-programmable gate array platforms: architectures and optimization techniques.

Hyeonseok Hong, Dahun Choi, Namjoon Kim, Haein Lee, Beom Jin Kang, Huibeom Kang, Hyun Kim

J. Real Time Image Process., May, 2024

HLQ: Hardware-Friendly Logarithmic Quantization Aware Training for Power-Efficient Low-Precision CNN Models.

Dahun Choi, Juntae Park, Hyun Kim

IEEE Access, 2024

ARC: Adaptive Rounding and Clipping Considering Gradient Distribution for Deep Convolutional Neural Network Training.

Dahun Choi, Hyun Kim

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

Mixed Precision Quantization with Hardware-Friendly Activation Functions for Hybrid ViT Models.

Beom Jin Kang, Dahun Choi, Hyun Kim

Proceedings of the International Conference on Electronics, Information, and Communication, 2024

GDS: Gradient Distribution Scaling-based Gradient Quantization for Low-complexity and Hardware-friendly Training of Instance Segmentation Models.

Dahun Choi, Hyun Kim

Proceedings of the International Conference on Electronics, Information, and Communication, 2024

SRU-Q: Hardware-friendly Stochastic Rounding Unit-based Gradient Quantization for CNN Training.

Sangbeom Jeong, Dahun Choi, Hyun Kim

Proceedings of the 6th IEEE International Conference on AI Circuits and Systems, 2024

2022

Hardware-Friendly Logarithmic Quantization with Mixed-Precision for MobileNetV2.

Dahun Choi, Hyun Kim

Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021

Hardware-friendly Log-scale Quantization for CNNs with Activation Functions Containing Negative Values.

Dahun Choi, Hyun Kim

Proceedings of the 18th International SoC Design Conference, 2021