Hugo Gangloff

According to our database, Hugo Gangloff authored at least 16 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Leveraging Satellite Data With Machine and Deep Learning Techniques for Corn Yield and Price Forecasting.

Florian Teste, Hugo Gangloff, Mathilde Chen, Philippe Ciais, David Makowski

IEEE Trans. Geosci. Remote. Sens., 2024

Self-Supervised Variational Autoencoder for Unsupervised Object Counting from Very-High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas.

Getachew Workineh Gella, Hugo Gangloff, Lorenz Wendt, Dirk Tiede, Stefan Lang

IEEE Trans. Geosci. Remote. Sens., 2024

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment.

Inass Soukarieh, Gerhard Hessler, Hervé Minoux, Marcel Mohr, K. Friedemann Schmidt, Jan Wenzel, Pierre Barbillon, Hugo Gangloff, Pierre Gloaguen

CoRR, 2024

2023

Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data.

Hugo Gangloff, Katherine Morales, Yohan Petetin

Comput. Stat. Data Anal., April, 2023

Object Counting from Aerial Remote Sensing Images: Application to Wildlife and Marine Mammals.

Tanya Singh, Hugo Gangloff, Minh-Tan Pham

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Weakly Supervised Marine Animal Detection from Remote Sensing Images Using Vector-Quantized Variational Autoencoder.

Minh-Tan Pham, Hugo Gangloff, Sébastien Lefèvre

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Variational Autoencoders for Unsupervised Object Counting from VHR Imagery: Applications in Dwelling Extraction from Forcibly Displaced People Settlement Areas.

Getachew Workineh Gella, Hugo Gangloff, Lorenz Wendt, Dirk Tiede, Stefan Lang

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Unsupervised Anomaly Detection Using Variational Autoencoder with Gaussian Random Field Prior.

Hugo Gangloff, Minh-Tan Pham, Luc Courtrai, Sébastien Lefèvre

Proceedings of the IEEE International Conference on Image Processing, 2023

2022

Leveraging Vector-Quantized Variational Autoencoder Inner Metrics for Anomaly Detection.

Hugo Gangloff, Minh-Tan Pham, Luc Courtrai, Sébastien Lefèvre

Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021

Unsupervised image segmentation with Gaussian Pairwise Markov Fields.

Hugo Gangloff, Jean-Baptiste Courbot, Emmanuel Monfrini, Christophe Collet

Comput. Stat. Data Anal., 2021

A General Parametrization Framework for Pairwise Markov Models: An Application to Unsupervised Image Segmentation.

Hugo Gangloff, Katherine Morales, Yohan Petetin

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Unsupervised Image Segmentation with Spatial Triplet Markov Trees.

Hugo Gangloff, Jean-Baptiste Courbot, Emmanuel Monfrini, Christophe Collet

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Probabilistic models for image processing: applications in vascular surgery. (Modèles probabilistes pour le traitement d'image: application à la chirurgie vasculaire).

Hugo Gangloff

PhD thesis, 2020

Improved centerline tracking for new descriptors of atherosclerotic aortas.

Hugo Gangloff, Emmanuel Monfrini, Mohamed Zied Ghariani, Mickaël Ohana, Christophe Collet, Nabil Chakfé

Proceedings of the Tenth International Conference on Image Processing Theory, 2020

Unsupervised segmentation of stents corrupted by artifacts in medical X-ray images.

Hugo Gangloff, Emmanuel Monfrini, Christophe Collet, Nabil Chakfé

Proceedings of the Tenth International Conference on Image Processing Theory, 2020

2018

Assessing the segmentation performance of pairwise and triplet Markov models.

Ivan Gorynin, Hugo Gangloff, Emmanuel Monfrini, Wojciech Pieczynski

Signal Process., 2018