AI on the Edge with CondenseNeXt: An Efficient Deep Neural Network for Devices with Constrained Computational Resources

AI on the Edge with CondenseNeXt: An Efficient Deep Neural Network for Devices with Constrained Computational Resources

Indiana University-Purdue University Indianapolis (IUPUI) === Research work presented within this thesis propose a neoteric variant of deep convolutional neural network architecture, CondenseNeXt, designed specifically for ARM-based embedded computing platforms with constrained computational resourc...

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Bibliographic Details
Main Author: Kalgaonkar, Priyank B.
Other Authors: El-Sharkawy, Mohamed A.
Language:en_US
Published: 2021
Subjects:
CondenseNeXt
edge
efficient
model
CIFAR10
CIFAR100
Python
PyTorch
Priyank Kalgaonkar
Image Processing
Computer Vision
Deep Learning
Neural Networks
AI
Image Classification
Machine Learning
Artificial Intelligence
CondenseNet
algorithm
CNN
DNN
ANN
NN
edge computing
Online Access:http://hdl.handle.net/1805/26438
http://dx.doi.org/10.7912/C2/64

Internet

http://hdl.handle.net/1805/26438
http://dx.doi.org/10.7912/C2/64

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