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agricultural-pattern-recognition

This project focuses on using the Semantic Segmentation Deep Learning architecture DeepLAbV3+ on the Agriculture-VIsion dataset. We focus on improving the architecture's performance by solving the class imbalance problem present in the data.

bovw-resnet18-robustness-evaluation

The aim of this project is to explore the classification of images using a ResNet18 Convolutional Neural Network and a Bag of Visual Words (BoVW) method that uses Support Vector Machines (SVM) on a dataset that contains 1200 224 x 224 images of cats and dogs.

data-generation-with-blender

Step-by-step tutorial on how to create data with Blender for an object detection application, with ressources included.

deformation_aware_embedding

Deformation-Aware 3D Model Embedding and Retrieval, ECCV 2020

evaluating-w-embeddings

In this paper we compare and evaluate two simple embedding models which can be constructed directly from a given co-occurrence matrix extracted from Twitter data; Positive Pointwise Mutual Information (PPMI), and Hellinger Principal Component Analysis (H-PCA). For each embedding model we consider three alternative metrics for word similarity: cosine, euclidean and manhattan distance.

optmizing-cnns-w-resnets

In this repository I explore the effect of applying Residual Connections to a VGG CNN Architecture, as well as applying Batch Normalisation. The networks are tested on the CIFAR100 benchmark dataset.

pca-on-fashion-mnist

This is a concise tutorial on applying PCA in the benchmark dataset Fashion MNIST. I analyse how the data compression process is done in visual information.

regularization-techniques-on-nns

During this study we will explore the different regularisation methods that can be used to address the problem of overfitting in a given Neural Network architecture, using the balanced EMNIST dataset.

svm-lr-on-fashion-mnist

This is a brief tutorial on using Logistic Regression and Support Vector Machines for classification on the Fashion MNIST dataset.

unsupervised-sdg-using-unity

wta_autoencoders

Initial implementation of Datasets that Are Not Paper, published in NeurIPS 2022.