Isabelle Eysseric's Projects
Gestionnaire d'agenda
Traitement automatique du langage naturel
Medical Image Segmentation and Anatomical Measurement Extraction with MATLAB & Python.
Face detection in augmented reality with face-api.js and Unity engines.
Classification of spectrogram images for the Kaggle competition: ''Birdcall Identification'' with Python.
Research internship in semantic segmentation for panoramic images.
Data analysis with R
Data science programs with Orange Data Mining app.
Application Ali Quebec
This is a container for ignition robotics version Fortress
High-level Ignition documentation that gets published to https://ignitionrobotics.org/docs/
Building image search an engine using MATLAB & Python.
Traitement de données massives: Analyse de sentiments sur les avis d'Amazon.
Minimal is a Jekyll theme for GitHub Pages
Create a moving object detection and tracking program using MATLAB & Python.
OCR System is a Python application that allows you to extract text from PDF documents, uploaded images, or images captured via a webcam. The application uses the Tesseract OCR library to recognize and extract text from images or PDF pages.
ProductsApiRestProject is a simple REST API interface built using ASP.NET Core to manage products and items in a retail or inventory system. This project implements CRUD (Create, Read, Update, Delete) operations for products and items, using .NET 8 technologies.
Building a Natural Language Question & Answer Search Engine with corpus in Python language.
Project goal: Have access to a simulator for doing research on mobile robotic control algorithms subject to adversarial conditions.
Sentiment analysis with dependency tree.
Specification and formal verification of traffic light control system.
Système intelligent à Base de Connaissances
Text Mining with Orange 3 and Python.
Recognition of Quebec road signs using transfer learning with Python.
Projets du club de Vehicules Autonomes de l'Université Laval (VAUL) en Robotique Mobile de la Faculté des Sciences et Génie de l'Université Laval.
Speech synthesis with conditioning on very small dataset. Using Nvidia's Tacotron2 and WaveGlow models with Pytorch.