I am a PhD student in Computer Science at ONERA and IRISA, supervised by Sébastien Lefèvre and Bertrand Le Saux. I teach computers how to look at airborne images to create beautiful maps. My research focuses on deep neural networks (deep learning) for remote sensing image analysis and Earth Observation. Specifically, I am currently working on convolutional neural networks for semantic labeling of airborne and satellite images (RGB, multi and hyperspectral).
I am interested in machine learning, algorithms and Python.
April 2017: Our Remote Sensing journal paper on vehicle segmentation for detection and classification is out in open access on the MPDI website.
March 2017: My colleague Alexandre Boulch will present the SnapNet architecture for semantic segmentation of unstructured point clouds at Eurographics 3DOR workshop. It is the current state-of-the-art on the Semantic3D dataset (code).
March 2017: Our paper on data fusion for remote sensing using deep nets won the 2nd best student paper award at JURSE 2017 ! Slides and poster are available.
Februrary 2017: The code of the deep network we used for the ISPRS Vaihingen 2D Semantic Labeling Challenge is out on Github !
January 2017: We will present two invited papers at JURSE 2017 !
November 2016: I will be at ACCV'16 in Taipei to present our poster on semantic segmentation of Earth Observation using multi-scale and multimodal deep networks.
October 2016: I will be at PyCon-fr (the French Python conference) to speak about deep learning using Python (slides (in French) and video (in French, too)).
September 2016: Our paper on the use of deep networks for object-based image analysis of vehicles in the ISPRS dataset has been distinguished by the "Best Benchmarking Contribution Award" at GEOBIA 2016 !
September 2016: I will be at GEOBIA 2016 in Enschede to talk about our work on object-based analysis of cars in remote sensing images using deep learning.
September 2016: Our paper on semantic segmentation for Earth Observation was accepted at ACCV'16 for a poster presentation. Check out the state-of-the-art results on the ISPRS Vaihingen 2D Semantic Labeling Challenge !
July 2016: I will be at IGARSS'16 in Beijing to present our work on superpixel-based semantic segmentation of aerial images.
April 2016: Our paper on region-based classification of remote sensing images using deep features has been accepted at IGARSS'16 for an oral presentation.
October 2015: I started as a PhD student at ONERA and IRISA.
PublicationsMost of my papers should be in open access on HAL or on arXiv.
- "Segment-before-Detect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images", Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Remote Sensing, MDPI, 2017.
- "Fusion of Heterogeneous Data in Convolutional Networks for Urban Semantic Labeling", Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, JURSE, Dubai, 2017 (slides, poster).
- "Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks", Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, ACCV, Taipei, 2016 (poster).
- "On the usability of deep networks for object-based image analysis", Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, GEOBIA, Enschede, 2016 (slides).
- "How useful is region-based classification of remote sensing images in a deep learning framework ?", Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, IGARSS, Beijing, 2016 (slides).
- "Structural classifiers for contextual semantic labeling of aerial images". Hicham Randrianarivo, Bertrand Le Saux, Nicolas Audebert, Michel Crucianu, Marin Ferecatu, Big Data from Space (BiDS), Tenerife, 2016.
- "Deep Learning for Remote Sensing". Nicolas Audebert, Alexandre Boulch, Adrien Lagrange, Bertrand Le Saux, Sébastien Lefèvre, 16th ONERA-DLR Aerospace Symposium (ODAS), Oberpfaffenhofen, 2016.
- "Deep learning for aerial cartography" (poster). Nicolas Audebert, Bertrand Le Saux, Sébastien Lefèvre, Statlearn Workshop, Vannes, 2016.
- Seminar @ IGN : Deep Learning for Multimodal Remote Sensing and Object Detection (21/03/2017)
- MS SIO @ CentraleSupélec : Deep Learning for Multimodal Remote Sensing and Object Detection (10/03/2017)
- PhD Students Day @ ONERA : Classification of Big Remote Sensing Data (30/01/2017)
- Seminar on GPU computing @ ONERA : GPU computing for deep learning (12/01/2017)
- PhD Students Day @ IRISA : Classification of Big Remote Sensing Data (08/12/2016)
- MATHIAS Conference @ TOTAL : Object-based classification of vehicles in aerial images using deep neural networks (28/10/2016)
- PyCon-FR : Deep learning with Python (15/10/2016)
- ODAS Conference @ ONERA & DLR : Deep learning for remote sensing (22/06/2016)
- Scientific workshop on image processing @ TOTAL : Deep learning for remote sensing (15/06/2016)
- STATLEARN conference @ Vannes : Deep learning for aerial cartography (poster) (07/04/2016)
ENPC : First year main course of C++ programming
ENPC : First year algorithmic and data structures
|2015 - today||PhD student -
"Classification of big remote sensing data"
Deep learning for image processing and Earth Observation
|ONERA, The French Aerospace Lab
Institute for Research in Computer Science and Random Systems (IRISA)
|2014 - 2015||Master Human-Computer Interaction||Université Paris-Sud|
|2012 - 2015||Engineering student - Computer Science||Supélec|
|2012 - 2013||Bachelor Mathematics||Université Paris-Sud|
|April 2015 - September 2015||Research internship||TUM - Computer Vision Lab||Deep learning for facial expression recognition|
|June 2014 - September 2014||Software Engineer (intern)||Withings||Web development of an incentive platform for quantified self (PHP/Backbone.js)|
|2012 - 2015||Member||Supélec Rézo||Sysadmin and software development for the organization providing Internet access to 700 students|
Skills :Programming :
- Advanced : Python (numpy, scipy, Caffe)
- Beginner : C, Java, OCaml
- Git, GIMP, Libre Office, LaTeX, GNU/Linux
- French (maternal)
- English (full proficiency)
- Japanese (beginner)
- German (beginner)
I graduated in 2015 from Supélec, one of France's top engineering school, with a focus on Computer Science. I also graduated from the université Paris-Sud with a MSc in Human-Computer Science. While I was an engineering student, I was head of the Supélec Rézo organization that provides Internet access to all Supélec' students.
Before this, I studied applied and fundamental mathematics at Université Paris-Sud and spent three years in preparation classes for the competitive entrance to engineering schools at lycée Janson-de-Sailly (Paris), with a heavy focus on maths and physics.
During the summer 2014, I interned in Withings' Platform team (web development/data analysis) where I designed and implemented an automated incentive system to help people take care of their health (PHP/Backbone.js).
I did my final intership in the Computer Vision lab at TUM under Pr. Daniel Cremers supervision. I worked on deep learning for facial expression recognition.
Since October 2015, I am a PhD student at ONERA.