1.1k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementFR33 papers
- Centre National de la Recherche ScientifiqueFR23 papers
- Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementFR20 papers
- AgroParisTechFR16 papers
- Université de MontpellierFR13 papers
- Institute for Cross-Disciplinary Physics and Complex SystemsES7 papers
- Laboratoire d'Informatique, de Robotique et de Microélectronique de MontpellierFR6 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR5 papers
- Universitat de les Illes BalearsES4 papers
- Aix-Marseille UniversitéFR3 papers
- CEA Paris-SaclayFR3 papers
- Centre de physique des particules de MarseilleFR3 papers
53 papers
Multi-modal Co-learning for Earth Observation: Enhancing single-modality models via modality collaboration
Francisco Mena, Dino Ienco, Cassio F. Dantas +2
Multi-modal co-learning is emerging as an effective paradigm in machine learning, enabling models to collaboratively learn from different modalities to enhance single-modality pred…
Fire severity and recovery across Europe: insights from forest diversity and landscape metrics
Eatidal Amin, Cassio F. Dantas, Dino Ienco +2
In recent decades, European forests have faced an increased incidence of fire disturbances. This phenomenon is likely to persist, given the rising frequency of extreme events expec…
TimeSenCLIP: A Time Series Vision-Language Model for Remote Sensing
Pallavi Jain, Diego Marcos, Dino Ienco +2
Vision-language models (VLMs) have shown significant promise in remote sensing applications, particularly for land-use and land-cover (LULC) mapping via zero-shot classification an…
Adaptations of AI models for querying the LandMatrix database in natural language
Fatiha Ait Kbir, Jérémy Bourgoin, Rémy Decoupes +2
The Land Matrix initiative (https://landmatrix.org) and its global observatory aim to provide reliable data on large-scale land acquisitions to inform debates and actions in sector…
Natural Language Querying System Through Entity Enrichment
Joshua Amavi, Mirian Halfeld Ferrari, Nicolas Hiot
This paper focuses on a domain expert querying system over databases. It presents a solution designed for a French enterprise interested in offering a natural language interface fo…
DisCoM-KD: Cross-Modal Knowledge Distillation via Disentanglement Representation and Adversarial Learning
Dino Ienco, Cassio Fraga Dantas
Cross-modal knowledge distillation (CMKD) refers to the scenario in which a learning framework must handle training and test data that exhibit a modality mismatch, more precisely,…
Open-Canopy: Towards Very High Resolution Forest Monitoring
Fajwel Fogel, Yohann Perron, Nikola Besic +8
Estimating canopy height and its changes at meter resolution from satellite imagery is a significant challenge in computer vision with critical environmental applications. However,…
Cartographie de l'habitat de reproduction du tétras-lyre (Lyrurus tetrix) dans les Alpes françaises
Alexandre Defossez, Samuel Alleaume, Marc Montadert +2
The Black Grouse (Lyrurus tetrix) is an emblematic alpine species with high conservation importance. The population size of these mountain bird tends to decline on the reference si…
Taec: a Manually annotated text dataset for trait and phenotype extraction and entity linking in wheat breeding literature
Claire Nédellec, Clara Sauvion, Robert Bossy +2
Wheat varieties show a large diversity of traits and phenotypes. Linking them to genetic variability is essential for shorter and more efficient wheat breeding programs. Newly desi…
Mapping mobile service usage diversity in cities
Maxime Lenormand
The ubiquitous use of mobile devices and associated Internet services generates vast volumes of geolocated data, offering valuable insights into human behaviors and their interacti…
Multimodality for improved CNN photometric redshifts
R. Ait-Ouahmed, S. Arnouts, J. Pasquet +2
Photometric redshift estimation plays a crucial role in modern cosmological surveys for studying the universe's large-scale structures and the evolution of galaxies. Deep learning…
Vision Transformers, a new approach for high-resolution and large-scale mapping of canopy heights
Ibrahim Fayad, Philippe Ciais, Martin Schwartz +8
Accurate and timely monitoring of forest canopy heights is critical for assessing forest dynamics, biodiversity, carbon sequestration as well as forest degradation and deforestatio…
Astronomical image time series classification using CONVolutional attENTION (ConvEntion)
Anass Bairouk, Marc Chaumont, Dominique Fouchez +3
Aims. The treatment of astronomical image time series has won increasing attention in recent years. Indeed, numerous surveys following up on transient objects are in progress or un…
An evaluation framework for comparing epidemic intelligence systems
Nejat Arinik, Roberto Interdonato, Mathieu Roche +1
In the context of Epidemic Intelligence, many Event-Based Surveillance (EBS) systems have been proposed in the literature to promote the early identification and characterization o…
High-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach
Martin Schwartz, Philippe Ciais, Catherine Ottlé +11
In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) i…
Habitat connectivity in agricultural landscapes improving multi-functionality of constructed wetlands as nature-based solutions
Clémentine Préau, Julien Tournebize, Maxime Lenormand +3
The prevention of biodiversity loss in agricultural landscapes to protect ecosystem stability and functions is of major importance in itself and for the maintenance of associated e…
Photometric Redshift Estimation with Convolutional Neural Networks and Galaxy Images: A Case Study of Resolving Biases in Data-Driven Methods
Q. Lin, D. Fouchez, J. Pasquet +4
Deep Learning models have been increasingly exploited in astrophysical studies, yet such data-driven algorithms are prone to producing biased outputs detrimental for subsequent ana…
Accelerating Non-Negative and Bounded-Variable Linear Regression Algorithms with Safe Screening
Cassio F. Dantas, Emmanuel Soubies, Cédric Févotte
Non-negative and bounded-variable linear regression problems arise in a variety of applications in machine learning and signal processing. In this paper, we propose a technique to…
Protection gaps in Amazon floodplains will increase with climate change: Insight from the world's largest scaled freshwater fish
Nicolas Dubos, Maxime Lenormand, Leandro Castello +3
The Amazon floodplains represent important surfaces of highly valuable ecosystems, yet they remain neglected from protected areas. While the efficiency of the protected area networ…
Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale
Larisa Lee-Cruz, Maxime Lenormand, Julien Cappelle +6
The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, wer…
Intersectional approach of everyday geography
Julie Vallée, Maxime Lenormand
Hour-by-hour variations in spatial distribution of gender, age and social class within cities remain poorly explored and combined in the segregation literature mainly centered on h…
Dispersal-based species pools as sources of connectivity area mismatches
Clémentine Préau, Nicolas Dubos, Maxime Lenormand +4
Context - Prioritising is likely to differ depending on the species considered for connectivity assessments, leading to a lack of consensual decisions for territorial planning. Obj…
Uncovering the socioeconomic structure of spatial and social interactions in cities
Maxime Lenormand, Horacio Samaniego
The relationship between urban mobility, social networks and socioeconomic status is complex and difficult to apprehend, notably due to the lack of data. Here we use mobile phone d…
Channel-Based Attention for LCC Using Sentinel-2 Time Series
Hermann Courteille, A. Benoît, N Méger +2
Deep Neural Networks (DNNs) are getting increasing attention to deal with Land Cover Classification (LCC) relying on Satellite Image Time Series (SITS). Though high performances ca…