Jurandy Almeida
Jurandy Almeida
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Visual Computing
Video Understanding through Deep Learning with Minimal Human Supervision
This project aims to investigate and propose methods to improve the generalization ability of deep learning in video understanding tasks, aiming to reduce the need for human supervision.
Sustainable Deep Learning for the Development of Autonomous Computational Intelligences
This project aims to investigate and propose methods to reduce the computational and human burden of deep learning in order to enable the development of more powerful Autonomous Computational Intelligences (ACIs).
Semantic Information Retrieval in Large Video Databases
This project aims to address practical and theoretical aspects of a multimodal information representation by exploiting recent solutions in visual computing and machine intelligence to efficiently combine different data modalities.
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