As a French Ph.D. student, I am passionate to whatever comes close to Artificial Intelligence & Earth Observation. Whether it is theoretical content with exploring state-of-the-art models or more concrete applicative programming with Jupyter Notebooks, I always find myself curious about what the world is up to !
Additionally, I am currently exploring the depth of SAR imagery seeing how it can help to better monitor forests.
SAR-iously studying is my motto. 😉
🛰️ 🛰️ 🛰️
PhD in Remote Sensing, 2020-2023
SONDRA Laboratory, CentraleSupélec, Gif-sur-Yvette, France; ONERA DTIS, Palaiseau, France
MSc in Artificial Intelligence & Multimodal Interaction, with Distinction, 2019-2020
Heriot-Watt University, Edinburgh, Scotland
Engineering degree in Computer Science, 2017-2020
EISTI, Cergy, France
BSc degree in Computer Science, 2015-2018
Cergy-Pontoise University, Cergy, France
Working on problematics of target detection in SAR Time Series of forests with the help of Deep Learning methods.
SONDRA Laboratory is a laboratory mixing 4 entities: Supélec (known today as CentraleSupélec), ONERA, the National University of Singapore and the DSO of Singapore.
As a deep learning Intern, I have trained, tuned and tested a model capable of doing building segmentation using satellite imagery. In this internship, I have tried multiple models (Mask RCNN, UNet, Deep UNet) and tried to take the best out of them all. The code was written using Keras with Tensorflow Back-End and was manipulated using a web-based RESTFul GUI with Flask and HTML5 technologies.
Also, multiple postprocessing technologies were considered and tried such as Logistic Regression (using scikit-learn) or Conditional Random Field (using pycrf).
A collection of earth observation-related posts about the beauties of Remote Sensing & our planet Earth.