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🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.
Learning Fine-grained Image Similarity with Deep Ranking is a novel application of neural networks, where the authors use a new multi scale architecture combined with a triplet loss to create a neural network that is able to perform image search. This repository is a simplified implementation of the same
tiny-imagenet dataset downloader & reader using tensorflow_datasets (tfds) api
This repository contains the jupyter notebooks for the custom-built DenseNet Model build on Tiny ImageNet dataset
Examples with ignite https://github.com/pytorch/ignite
a tensorflow based implementation of ShuffleNetV2 on the Tiny ImageNet dataset
:clipboard:This is a miniature of ImageNet classification Challenge.
Computer Vision: State of the Art model implementation using PyTorch framework.
Image Classification-Deep Learning-For Beginner
Repository for CSE 666: Biometrics course in SUNY Buffalo.