Jueun Jung

Orcid: 0000-0003-1632-159X

According to our database1, Jueun Jung authored at least 11 papers between 2020 and 2024.

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

Timeline

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Links

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Bibliography

2024
A Real-Time Sparsity-Aware 3D-CNN Processor for Mobile Hand Gesture Recognition.
IEEE Trans. Circuits Syst. I Regul. Pap., August, 2024

An Energy-Efficient, Unified CNN Accelerator for Real-Time Multi-Object Semantic Segmentation for Autonomous Vehicle.
IEEE Trans. Circuits Syst. I Regul. Pap., May, 2024

20.6 LSPU: A Fully Integrated Real-Time LiDAR-SLAM SoC with Point-Neural-Network Segmentation and Multi-Level kNN Acceleration.
Proceedings of the IEEE International Solid-State Circuits Conference, 2024

An Energy-Efficient 3D Point Neural Network Accelerator with Fine-grained LiDAR-SoC Pipeline Structure.
Proceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design, 2024

A 422.1 Mpixels/J Tile-based 4K Super Resolution Processor with Variable Bit Compression.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

LSPU: A 20.7 ms Low-Latency Point Neural Network-Based 3D Perception and Semantic LiDAR SLAM System-on-Chip for Autonomous Driving System.
Proceedings of the 36th IEEE Hot Chips Symposium, 2024

A Low-power and Real-time Semantic LiDAR SLAM Processor with Point Neural Network Segmentation and kNN Acceleration for Mobile Robots.
Proceedings of the IEEE Symposium in Low-Power and High-Speed Chips, 2024

2023
A Ternary Neural Network Computing-in-Memory Processor With 16T1C Bitcell Architecture.
IEEE Trans. Circuits Syst. II Express Briefs, May, 2023

2022
An Energy-Efficient CNN Accelerator for Multi-object Real-Time Semantic Segmentation in Autonomous Vehicle.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

A Real-Time Sparsity-Aware 3D-CNN Processor for Mobile Hand Gesture Recognition.
Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2020
An Energy-Efficient Deep Neural Network Accelerator Design.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020


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