This repository contains a PyTorch implementation for classifying the Oxford IIIT Pet Dataset using KNN and ResNet. The goal is to differentiate the results obtained using these two approaches.
-
Updated
Jan 2, 2024 - Jupyter Notebook
This repository contains a PyTorch implementation for classifying the Oxford IIIT Pet Dataset using KNN and ResNet. The goal is to differentiate the results obtained using these two approaches.
Image segmentation on the oxford-iiit pet dataset using CNN's, GNN's and U-Nets
Training a Convolutional Neural Network to perform Image Segmentation on Oxford Pets Dataset
Semantic Image Segmentation task solution for the Oxford-IIIT Pet dataset using U-Net neural network, Hyperband and Transfer Learning. AGH 2023/24
Training CNN based image classifiers to identify breeds of cats and dogs.
A dataset created using some images from the Oxford-IIIT Pet dataset, and then performing some data augmentation and processing
CNN for classifying the breed of cats and dogs in the Oxford-IIIT Pet Dataset
Deep learning-based segmentation with U-Net architecture on Oxford-IIIT Pet dataset, leveraging VGG16 model.
Image segmentation task for IIIT-Oxford Pets Dataset. Develops and compares various segmentation architectures. Also introduces important utility functions.
Add a description, image, and links to the oxford-iiit-pets-dataset topic page so that developers can more easily learn about it.
To associate your repository with the oxford-iiit-pets-dataset topic, visit your repo's landing page and select "manage topics."