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Sara Costa Freitas
Assistant Researcher
PhD in Electrical and Computer Engineering from the University of Porto (Faculdade de Engenharia), and MSc in Electrical and Electronic Engineering - Autonomous Systems branch from ISEP Porto Polytechnic School. Since 2016 she has been a researcher at CRAS – INESC TEC, where she works with hyperspectral cameras, mainly in classification algorithms using deep learning techniques and unsupervised approaches. The main topic of her PhD thesis was to detect and classify marine litter using different machine learning and deep learning methods, which culminated in implementing the first zero-shot learning algorithm with hyperspectral imaging data. She also made part of the team that collected the datasets used to implement these algorithms in a real hotspot, using manned and unmanned aircraft. At the moment, she is working as an assistant researcher In the NewSpace Project (PT-PRR), in the development of novel AI methods for data compression onboard satellites.
Publications
Hyperspectral Imaging Zero-Shot Learning for Remote Marine Litter Detection and Classification
Freitas, S;Silva, H;Silva, E;
2022
REMOTE SENSING
Remote Hyperspectral Imaging Acquisition and Characterization for Marine Litter Detection
Freitas, S;Silva, H;Silva, E;
2021
REMOTE SENSING
Supervised vs Unsupervised Approaches for Real Time Hyperspectral Imaging Maritime Target Detection
Freitas, S;Silva, H;Almeida, J;Martins, A;Silva, E;
2018
2018 OCEANS - MTS/IEEE KOBE TECHNO-OCEANS (OTO)
Convolutional neural network target detection in hyperspectral imaging for maritime surveillance
Freitas, S;Silva, H;Almeida, JM;Silva, E;
2019
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
