We investigate how a deep learning approach in AI can help streamline and automate the scanning and modeling of 3D scenes and objects. This new 3D representation paradigm and format will revolutionize audiovisual production, from visual effects (VFX) and virtual production (ICVFX) to extended reality (XR) experiences and applications.
We investigate how geometric deep learning and graph neural networks can help accelerate the development of new drugs, taking into account the geometric information of molecules and not only their physicochemical and quantum description. This new approach to the discovery of drugs promises to reduce development times of new drugs from decades to months, focusing on neurodegenerative diseases such as ALS, multiple sclerosis, Parkinson’s disease or Alzheimer’s disease.
We investigate how deep learning-based computer vision methods can aid in the detection of sperm whale blows, for the early detection of the presence of these cetaceans on the surface. Maritime traffic represents a real threat to these key players in marine biodiversity, as traffic is becoming denser and ships faster.
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