Seokchan Song

Orcid: 0000-0002-4119-8936

According to our database1, Seokchan Song authored at least 14 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

2021
2022
2023
2024
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5
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Legend:

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In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
An Energy-Efficient CNN/Transformer Hybrid Neural Semantic Segmentation Processor With Chunk-Based Bit Plane Data Compression and Similarity-Based Token-Level Skipping Exploitation.
IEEE Trans. Circuits Syst. I Regul. Pap., December, 2024

NeRF-Navi: A 93.6-202.9µJ/task Switchable Approximate-Accurate NeRF Path Planning Processor with Dual Attention Engine and Outlier Bit-Offloading Core.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits 2024, 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

A 3.55 mJ/frame Energy-efficient Mixed-Transformer based Semantic Segmentation Accelerator for Mobile Devices.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

Space-Mate: A 303.5mW Real-Time NeRF SLAM Processor with Sparse-Mixture-of-Experts-based Acceleration.
Proceedings of the 36th IEEE Hot Chips Symposium, 2024

A Low-power and Real-time Neural-Rendering Dense SLAM Processor with 3-Level Hierarchical Sparsity Exploitation.
Proceedings of the IEEE Symposium in Low-Power and High-Speed Chips, 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


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