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Scarlett is passionate about applications of robotics and machine learning for environmental conservation. She is interested in underwater surveys of marine species on the Great Barrier Reef and improving automation with deep learning. Her PhD aims to develop a deep learning architecture which reduces the necessity for collecting and labelling large datasets of images for training a deep learning model.
Scarlett graduated from QUT with a Bachelor of Engineering (Mechatronics) with first class honours.
Publications:
Multi-species Seagrass Detection and Classification from Underwater Images (accepted to DICTA 2020)
Thesis:
Semi-supervised multimodal deep learning with Bayesian knowledge exploitation for classification of marine species in underwater imagery