Taewoo Kim

Orcid: 0000-0002-8608-9514

Affiliations:
  • Korea Advanced Institute of Science & Technology, Korea


According to our database1, Taewoo Kim authored at least 12 papers between 2018 and 2024.

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

Timeline

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Bibliography

2024
EPU: An Energy-Efficient Explainable AI Accelerator With Sparsity-Free Computation and Heat Map Compression/Pruning.
IEEE J. Solid State Circuits, March, 2024

2023
A Channel Pruning Optimization With Layer-Wise Sensitivity in a Single-Shot Manner Under Computational Constraints.
IEEE Access, 2023

Recursive Visual Explanations Mediation Scheme Based on DropAttention Model With Multiple Episodes Pool.
IEEE Access, 2023

SLO-Aware DL Job Scheduling for Efficient FPGA-GPU Edge Cloud Computing.
Proceedings of the Current Trends in Web Engineering, 2023

A 26.55TOPS/W Explainable AI Processor with Dynamic Workload Allocation and Heat Map Compression/Pruning.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2023

2022
Federated Onboard-Ground Station Computing With Weakly Supervised Cascading Pyramid Attention Network for Satellite Image Analysis.
IEEE Access, 2022

FleX: A Flex Interconnected HPC System With Stochastic Load Balancing Scheme.
IEEE Access, 2022

Event-guided Deblurring of Unknown Exposure Time Videos.
Proceedings of the Computer Vision - ECCV 2022, 2022

2020
Loop-Net: Joint Unsupervised Disparity and Optical Flow Estimation of Stereo Videos With Spatiotemporal Loop Consistency.
IEEE Robotics Autom. Lett., 2020

2019
DL-dashboard: user-friendly deep learning model development environment.
Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion, 2019

2018
IDLE: Integrated Deep Learning Engine with Adaptive Task Scheduling on Heterogeneous GPUs.
Proceedings of the TENCON 2018, 2018

An Adaptive Batch-Orchestration Algorithm for the Heterogeneous GPU Cluster Environment in Distributed Deep Learning System.
Proceedings of the 2018 IEEE International Conference on Big Data and Smart Computing, 2018


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