Deep ConvNet Image Classifier based on Residual Network architecture trained on Caltech 101 Object Dataset

Replication of DeCAF paper's experiments for transfer learning

This repository contains the implementation of a fault detection system that detects and eliminates faulty products based on shape and color using a Convolutional Neural Network (CNN).

My Deep Learning Work

CNN-based image classification

Image Classification using Machine Learning, Neural Nets and CNNs.

Imperial College London EE4-62 Machine Learning for Computer Vision Coursework 1

Image recognition on CIFAR 10, CIFAR 100, Caltech 101 and Caltech 256 datasets. With the implementation of WideResNet, InceptionV3 and DenseNet neural networks.

Reimplementation of "VAE with a VampPrior" by Jakub M. Tomczak et al., as part of the DD2434 Machine Learning, Advanced Course at KTH

PyTorch Tutorials for several cases

Pytorch Implementations of Neural Networks

Image Classification performed in HistogramData

Content-Based Image Retrieval Using CNN and Hash