Pruning Convolution Neural Network (SqueezeNet) for Efficient Hardware Deployment

Pruning Convolution Neural Network (SqueezeNet) for Efficient Hardware Deployment

Indiana University-Purdue University Indianapolis (IUPUI) === In recent years, deep learning models have become popular in the real-time embedded application, but there are many complexities for hardware deployment because of limited resources such as memory, computational power, and energy. Recent...

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Bibliographic Details
Main Author: Gaikwad, Akash S.
Other Authors: El-Sharkawy, Mohamed
Language:en_US
Published: 2018
Subjects:
Convolution neural network
CNN
SqueezeNet
Pruning
L2 Normalization
CIFAR-10
Transfer learning
Coarse pruning
S32V234
Taylor expansion
RTMaps
BlueBox
Fine pruning
Model compression
Activation maps
Online Access:http://hdl.handle.net/1805/17923

Internet

http://hdl.handle.net/1805/17923

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