Seokchan Song
Orcid: 0000-0002-4119-8936
According to our database1,
Seokchan Song
authored at least 9 papers
between 2021 and 2024.
Collaborative distances:
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Bibliography
2024
20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing.
Proceedings of the IEEE International Solid-State Circuits Conference, 2024
2023
GPPU: A 330.4-μJ/ task Neural Path Planning Processor with Hybrid GNN Acceleration for Autonomous 3D Navigation.
Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023
2022
A 49.5 mW Multi-Scale Linear Quantized Online Learning Processor for Real-Time Adaptive Object Detection.
IEEE Trans. Circuits Syst. II Express Briefs, 2022
A Mobile DNN Training Processor With Automatic Bit Precision Search and Fine-Grained Sparsity Exploitation.
IEEE Micro, 2022
HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Mobile Devices.
Proceedings of the 2022 IEEE Hot Chips 34 Symposium, 2022
A DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022
A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022
2021
HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-Point and Active Bit-Precision Searching.
IEEE J. Solid State Circuits, 2021
An Energy-Efficient Deep Neural Network Training Processor with Bit-Slice-Level Reconfigurability and Sparsity Exploitation.
Proceedings of the IEEE Symposium in Low-Power and High-Speed Chips, 2021