Sylvain Lobry

Orcid: 0000-0003-4738-2416

Affiliations:
  • Université de Paris, France


According to our database1, Sylvain Lobry authored at least 43 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Domain Adaptation for Mapping LCZs in Sub-Saharan Africa With Remote Sensing: A Comprehensive Approach to Health Data Analysis.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

An LLM Agent for Automatic Geospatial Data Analysis.
CoRR, 2024

Can SAR improve RSVQA performance?
CoRR, 2024

Can we detect plant diseases without prior knowledge of their existence?
Int. J. Appl. Earth Obs. Geoinformation, 2024

Segmentation-Guided Attention for Visual Question Answering from Remote Sensing Images.
Proceedings of the IGARSS 2024, 2024

2023
The curse of language biases in remote sensing VQA: the role of spatial attributes, language diversity, and the need for clear evaluation.
CoRR, 2023

Deep learning for classification of noisy QR codes.
CoRR, 2023

Seasonal semi-supervised domain adaptation for linking population studies and Local Climate Zones.
Proceedings of the Joint Urban Remote Sensing Event, 2023

Automatic Simulation of SAR Images: Comparing a Deep-Learning Based Method to a Hybrid Method.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Transforming Multidimensional Data into Images to Overcome the Curse of Dimensionality.
Proceedings of the IEEE International Conference on Image Processing, 2023

An a contrario approach for plant disease detection.
Proceedings of the 34th British Machine Vision Conference Workshop Proceedings, 2023

Multi-task prompt-RSVQA to explicitly count objects on aerial images.
Proceedings of the 34th British Machine Vision Conference Workshop Proceedings, 2023

2022
Remote Sensing VQA - High Resolution (RSVQA HR).
Dataset, March, 2022

Remote Sensing VQA - Low Resolution (RSVQA LR).
Dataset, March, 2022

Wasserstein Adversarial Regularization for Learning With Label Noise.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Language Transformers for Remote Sensing Visual Question Answering.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

Embedding Spatial Relations in Visual Question Answering for Remote Sensing.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Prompt-RSVQA: Prompting visual context to a language model for Remote Sensing Visual Question Answering.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
RSVQAxBEN.
Dataset, July, 2021

RSVQAxBEN.
Dataset, July, 2021

How to find a good image-text embedding for remote sensing visual question answering?
Proceedings of MACLEAN: MAChine Learning for EArth ObservatioN Workshop co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2021), 2021

RSVQA Meets Bigearthnet: A New, Large-Scale, Visual Question Answering Dataset for Remote Sensing.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
RSVQA: Visual Question Answering for Remote Sensing Data.
IEEE Trans. Geosci. Remote. Sens., 2020

Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data.
Int. J. Geogr. Inf. Sci., 2020

Interpretable Scenicness from Sentinel-2 Imagery.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Learning Multi-Label Aerial Image Classification Under Label Noise: A Regularization Approach Using Word Embeddings.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Contextual Semantic Interpretability.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery Using Deep CNNs and Active Learning.
IEEE Trans. Geosci. Remote. Sens., 2019

Water Detection in SWOT HR Images Based on Multiple Markov Random Fields.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019

Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise.
CoRR, 2019

Correcting rural building annotations in OpenStreetMap using convolutional neural networks.
CoRR, 2019

Deep Learning Models to Count Buildings in High-Resolution Overhead Images.
Proceedings of the Joint Urban Remote Sensing Event, 2019

Visual Question Answering From Remote Sensing Images.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Semantically Interpretable Activation Maps: what-where-how explanations within CNNs.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Scale equivariance in CNNs with vector fields.
CoRR, 2018

Correcting Misaligned Rural Building Annotations in Open Street Map Using Convolutional Neural Networks Evidence.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Modèles Markoviens pour les images SAR : application à la détection de l'eau dans les images satellitaires SWOT et analyse multi-temporelle de zones urbaines. (Markovian models for SAR images : application to water detection in SWOT satellite images and multi-temporal analysis of urban areas).
PhD thesis, 2017

Urban area change detection based on generalized likelihood ratio test.
Proceedings of the 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2017

Unsupervised detection of thin water surfaces in SWOT images based on segment detection and connection.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

Double MRF for water classification in SAR images by joint detection and reflectivity estimation.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

2016
Multitemporal SAR Image Decomposition into Strong Scatterers, Background, and Speckle.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016

A decomposition model for scatterers change detection in multi-temporal series of SAR images.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

2015
Sparse + smooth decomposition models for multi-temporal SAR images.
Proceedings of the 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images, 2015


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