Sobre o Evento
In the last decades, a debate on a responsible, sustainable human presence on Earth emerged strongly. With climate change and the overwhelming economic pressure on Nature, empowering procedures for efficient resource use with the recent advances in artificial intelligence is vital to create adequate policies and trigger warning alerts accordingly. Remotely sensing natural dynamic phenomena, like phenological crop cycles or deforestation processes, is challenging. Continuous and smooth physical processes usually rule such phenomena, but remote sensing involves different sensors with very different essence, scale, and visit rates, corrupted by stochastic events, resulting in highly complex multimodal multitemporal and multi-scale datasets. Moreover, data labeling in Earth Observation (EO) applications is usually scarce or unavailable due to the massive amount of data continuously acquired or notorious fieldwork limitations. This presentation discusses machine learning approaches for earth observation data with scarce labeling, aiming to develop environmental protection solutions, promote efficient tools to adapt to EO's global warming effects, and support efficient agricultural practices with a lower data annotation burden.
Texto informado pelo autor.
* Os participantes dos seminários não poderão acessar às dependências da FGV usando bermuda, chinelos, blusa modelo top ou cropped, minissaia ou camiseta regata. O uso da máscara é facultativo, porém é obrigatória a apresentação do comprovante de vacinação (físico ou digital).
Apoiadores / Parceiros / Patrocinadores
Dário Oliveira - received his M.Sc. (2009) and Ph.D. (2013) degrees in Electrical Engineering from the Pontifical Catholic University of Rio de Janeiro, Brazil. He was a visiting scholar at the Instituto Superior Técnico in Lisbon, Portugal (2008-2009) and the Leibniz University of Hannover in Germany (2011-2012). As a postdoctoral fellow, he studied machine learning applied to neuroscience at the University of Sao Paulo, Brazil (2014-2015) and applied to dairy science at the University of Wisconsin, USA (2020-2021). From 2015 to 2021, he worked in the industry at the General Electric Global Research Center in Rio de Janeiro and later at the IBM Research lab in São Paulo, Brazil. From 2021 to 2022 he worked as a Guest Professor at the AI4EO lab at the Technical University of Munich, Germany. He currently works at the School of Applied Mathematics, Getulio Vargas Foundation, Rio de Janeiro, Brazil.
a) Opção presencial *
Praia de Botafogo, 190
5o andar, Auditório 537
b) Opção remota (via Zoom)
Meeting ID: 981 5075 6795
Tel: 55 21 3799-5917