GitHub / jagennath-hari / ResNet5M-CIFAR10
The main goal of this project is to come up with an architecture having the highest test accuracy on the CIFAR-10 image classification dataset, under the constraint that model has no more than 5 million parameters.
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PURL: pkg:github/jagennath-hari/ResNet5M-CIFAR10
Fork of navoday01/ResNet5M-CIFAR10
Stars: 0
Forks: 0
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 168 MB
Dependencies parsed at: Pending
Created at: over 2 years ago
Updated at: over 2 years ago
Pushed at: over 2 years ago
Last synced at: over 2 years ago
Topics: cifar-10, deep-learning, image-classification, neural-network, python, pytorch, resnet, skip-connections