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DTSTART;TZID=Europe/Paris:20231011T100000
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DTSTAMP:20260531T160651
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LAST-MODIFIED:20231006T121251Z
UID:8725-1697018400-1697047200@datacraft.paris
SUMMARY:PARIS WORKSHOP - Frugal AI techniques applied to Image Semantic Segmentation
DESCRIPTION:Inscription\n                \n            \n            \n			\n				\n				\n				\n				\n				Machine Learning prerequisites** : Good skills \nPython prerequisites** : Good skills \nTechnical prerequisitesBring your own laptop \nSpeakersThis workshop will be animated by : \n\nDenis Marraud\, Image Processing Senior Expert\, Airbus Defence and Space\n\nWorkshop overviewFollowing the Frugal AI overview workshop organized in May\, this next workshop will aim at putting in practice and comparing the interest of some relevant Frugal AI techniques to solve a domain adaptation problem for one or several image semantic segmentation tasks. The cost and complexity of dense annotations required for this task makes it particularly interesting to leverage any technique contributing to the reduction of the number of required manual annotations.Envisaged techniques may include advanced data augmentation and pseudo-labelling methods\, weakly supervised or self-supervised methods. Various domain adaptation tasks may be considered : either domain specialization (or transductive learning) where the test domain is known in advance and closed\, domain extension where the performance should be optimized for both source and target domain\, or domain adaptation where the performance should be optimized on the target domain only. \nDataset descriptionExtracts from publicly available image segmentation datasets will be delivered to the participants. These datasets will cover various application domains such as medical imagery\, satellite or aerial imagery and self driving car imagery. \nAlgorithmic methodsAmong the techniques that could be tested during this workshop : \n\nAdvanced data augmentation methods (based on existing libraries)\nAdvanced pseudo-labelling methods (making use of non annotated data)\nSelf-supervised methods (e.g. contrastive learning\, predictive learning) as a pre-training step\nTest time adaptation methods to adapt to local context
URL:https://datacraft.paris/event/frugal-ai-techniques-applied-to-image-semantic-segmentation/
LOCATION:datacraft –\, 3 rue Rossini\, 75009 Paris\, France
CATEGORIES:- Event in English -,on-site event
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