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PhD (Cifre contract) on Object Detection from Few Multispectral Examples

9 Février 2023

Catégorie : Doctorant

Academic lab: IRISA (
Compagny: ATERMES(
Contract: CIFRE PHD

The project aims at providing deep learning-based methods to detect objects in outdoor environments using multispectral data in a low supervision context, e.g., learning from few examples to detect scarcely-observed objects. The data consist of RGB and IR (Infra-red) images which are frames from calibrated and aligned multispectral videos.

Few-shot learning [1][2], active learning [3] and incremental/continual learning [4][5] are among the frameworks to be investigated since they allow to limit the number of labeled examples needed for learning. Most developed methods [6][7][8][9] based on these approaches have been proposed to perform object detection from RGB images within different weakly-supervised scenarios. They should be adapted and improved to deal with scarce object detection from multispectral images.In case of lacking objects of interest during the training, anomaly detection approaches [10][11] can be also considered to detect new object classes which will be further characterized by prior semantic concepts.
More information about the PhD topic and the Application process, please visit: