I have used the All-CNN network published in the 2015 ICLR paper, "Striving For Simplicity: The All Convolutional Net". This paper can be found at the following link: https://arxiv.org/pdf/1412.6806.pdf The dataset I have used is the CIFAR-10 dataset, which consists of 60,000 32x32 color images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
-
Notifications
You must be signed in to change notification settings - Fork 1
Kashi7/Object-Recognition
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Object recognition using cifar10 dataset
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published