Convolutional Neural Network

An n-dimensional convolutional neural network (CNN), written from scratch in Julia.

PDE-based Group Equivariant CNNs for PyTorch

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My MSc thesis work. I essayed with a number of classifiers for two type of health-related time series: electrocardiogram and blood oxygen levels. The four approaches used on each type of signal were: (i) featured based approach, where integral and differential attributes where devised and used to classify the sets (ii) Direct Machine Learning application to the time series (Perceptron, Random Forest and others) (iii) 1D convolutional neural networks applied to the signals (iv) 2D convolutional neural networks applied to the signal spectrograms.

The thesis pdf file, included here, is written in Spanish.

A companion project to https://gitlab.com/sambryant/rosy-public for training feature tagged image datasets using RCNN from PyTorch.

A real-time human counting system with age and gender classification.

Face Authenticator

Computation of cyclist trajectories on tracks using videos. Research carried out in an innovation laboratory for the French Olympic track cyclism team (2022).

Detection of bike wheels on images using neural networks. Research carried out in an innovation laboratory for the French Olympic track cyclism team (2022).

Study and development of two neural network architectures for extreme ultraviolet pulse reconstruction

Multimodal Brain Tumor Segmentation (BRATS) Challenge 2019

Training of deep networks for medical image segmentation tasks Network and training strategy that relies on the strong use of data augmentation

Haruspex is a Convolutional Neural Network capable of recognizing and predicting secondary structure elements and nucleotides in Cryo-EM reconstruction density.

This project deals with training of convolutional neural network for licence plate detection in video. Darknet technology was used for detection, specifically the YOLOv3-tiny neural network model.