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A comprehensive review of model compression techniques in machine learning
This paper critically examines model compression techniques within the machine learning
(ML) domain, emphasizing their role in enhancing model efficiency for deployment in …
(ML) domain, emphasizing their role in enhancing model efficiency for deployment in …
Neuromorphic computing using NAND flash memory architecture with pulse width modulation scheme
A novel operation scheme is proposed for high-density and highly robust neuromorphic
computing based on NAND flash memory architecture. Analog input is represented with time …
computing based on NAND flash memory architecture. Analog input is represented with time …
[HTML][HTML] Investigation of deep spiking neural networks utilizing gated Schottky diode as synaptic devices
Deep learning produces a remarkable performance in various applications such as image
classification and speech recognition. However, state-of-the-art deep neural networks …
classification and speech recognition. However, state-of-the-art deep neural networks …
Memristive crossbar circuit for neural network and its application in digit recognition
X Wan, N He, D Liang, W Xu, L Wang… - Japanese Journal of …, 2022 - iopscience.iop.org
A neural network fully implemented by memristive crossbar circuit is proposed and
simulated, which can operate in parallel for the entire process. During the forward …
simulated, which can operate in parallel for the entire process. During the forward …
[CITA][C] Structured pruning 을 활용한 hardware spiking neural network 경량화
전보성， 장태진， 박병국 - 대한전자공학회 학술대회, 2022 - dbpia.co.kr
In this paper, we evaluate a structured pruning to compress the hardware-based spiking
neural network (SNN). Since CMOS neuron circuit has a larger area than the synaptic …
neural network (SNN). Since CMOS neuron circuit has a larger area than the synaptic …