Jong-Ho Lee
Orcid: 0000-0003-3559-9802Affiliations:
- Seoul National University, South Korea Ministry of Science and ICT, South Korea
- Seoul National University, Department of Electrical and Computer Engineering / Inter-University Semiconductor Research Center, South Korea
- Massachusetts Institute of Technology, Cambridge, MA, USA (1998 - 1999)
- Seoul National University, South Korea (PhD 1993)
According to our database1,
Jong-Ho Lee
authored at least 37 papers
between 2013 and 2025.
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Collaborative distances:
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Online presence:
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Bibliography
2025
Efficient Hybrid Training Method for Neuromorphic Hardware Using Analog Nonvolatile Memory.
IEEE Trans. Neural Networks Learn. Syst., January, 2025
2024
Toward Optimized In-Memory Reinforcement Learning: Leveraging 1/<i>f</i> Noise of Synaptic Ferroelectric Field-Effect-Transistors for Efficient Exploration.
Adv. Intell. Syst., June, 2024
SNNSim: Investigation and Optimization of Large-Scale Analog Spiking Neural Networks Based on Flash Memory Devices.
Adv. Intell. Syst., April, 2024
Si-Based Dual-Gate Field-Effect Transistor Array for Low-Power On-Chip Trainable Hardware Neural Networks.
Adv. Intell. Syst., January, 2024
2023
Analog Synaptic Devices Based on IGZO Thin-Film Transistors with a Metal-Ferroelectric-Metal-Insulator-Semiconductor Structure for High-Performance Neuromorphic Systems.
Adv. Intell. Syst., December, 2023
1/<i>f</i> Noise in Synaptic Ferroelectric Tunnel Junction: Impact on Convolutional Neural Network.
Adv. Intell. Syst., June, 2023
2022
Novel, parallel and differential synaptic architecture based on NAND flash memory for high-density and highly-reliable binary neural networks.
Neurocomputing, 2022
Neuron Circuits for Low-Power Spiking Neural Networks Using Time-To-First-Spike Encoding.
IEEE Access, 2022
IEEE Access, 2022
Proceedings of the IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits 2022), 2022
3D-FPIM: An Extreme Energy-Efficient DNN Acceleration System Using 3D NAND Flash-Based In-Situ PIM Unit.
Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022
Proceedings of the IEEE International Symposium on Olfaction and Electronic Nose, 2022
Proceedings of the IEEE International Symposium on Olfaction and Electronic Nose, 2022
2021
On-chip trainable hardware-based deep Q-networks approximating a backpropagation algorithm.
Neural Comput. Appl., 2021
Hardware-based spiking neural network architecture using simplified backpropagation algorithm and homeostasis functionality.
Neurocomputing, 2021
CoRR, 2021
Direct Gradient Calculation: Simple and Variation-Tolerant On-Chip Training Method for Neural Networks.
Adv. Intell. Syst., 2021
IEEE Access, 2021
Spiking Neural Networks With Time-to-First-Spike Coding Using TFT-Type Synaptic Device Model.
IEEE Access, 2021
Hardware-Based Spiking Neural Network Using a TFT-Type AND Flash Memory Array Architecture Based on Direct Feedback Alignment.
IEEE Access, 2021
2020
Efficient precise weight tuning protocol considering variation of the synaptic devices and target accuracy.
Neurocomputing, 2020
Hardware Implementation of Spiking Neural Networks Using Time-To-First-Spike Encoding.
CoRR, 2020
Low-Power and High-Density Neuron Device for Simultaneous Processing of Excitatory and Inhibitory Signals in Neuromorphic Systems.
IEEE Access, 2020
Double-Gated Asymmetric Floating-Gate-Based Synaptic Device for Effective Performance Enhancement Through Online Learning.
IEEE Access, 2020
Low-Power Binary Neuron Circuit With Adjustable Threshold for Binary Neural Networks Using NAND Flash Memory.
IEEE Access, 2020
NAND Flash Based Novel Synaptic Architecture for Highly Robust and High-Density Quantized Neural Networks With Binary Neuron Activation of (1, 0).
IEEE Access, 2020
2019
Adaptive learning rule for hardware-based deep neural networks using electronic synapse devices.
Neural Comput. Appl., 2019
Accurate identification of gas type and concentration using DNN reflecting the sensing properties of MOSFET-type gas sensor.
Proceedings of the IEEE International Symposium on Olfaction and Electronic Nose, 2019
Investigation of Neural Networks Using Synapse Arrays Based on Gated Schottky Diodes.
Proceedings of the International Joint Conference on Neural Networks, 2019
A Spiking Neural Network with a Global Self-Controller for Unsupervised Learning Based on Spike-Timing-Dependent Plasticity Using Flash Memory Synaptic Devices.
Proceedings of the International Joint Conference on Neural Networks, 2019
Detection of Low Concentration NO2 gas Using Si FET-type Gas Sensor with Localized Micro-heater for Low Power Consumption.
Proceedings of the 2019 IEEE SENSORS, Montreal, QC, Canada, October 27-30, 2019, 2019
Proceedings of the 49th European Solid-State Device Research Conference, 2019
2018
Unsupervised Online Learning With Multiple Postsynaptic Neurons Based on Spike-Timing-Dependent Plasticity Using a TFT-Type NOR Flash Memory Array.
CoRR, 2018
A 16Gb 18Gb/S/pin GDDR6 DRAM with per-bit trainable single-ended DFE and PLL-less clocking.
Proceedings of the 2018 IEEE International Solid-State Circuits Conference, 2018
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018
2017
Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices.
CoRR, 2017
2013
IEICE Trans. Electron., 2013