Automatic detection of endangered species in video and satellite images using deep learning
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hdl:2117/347191
Document typeBachelor thesis
Date2021-04-27
Rights accessRestricted access - author's decision
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Abstract
A work on processing techniques using Deep Learning (Convolutional Neural Networks) to detect and classify marine mammals in aerial photographs. The computational capacity offered by these new tools will allow the scientific community to better study endangered species and to give an adequate and rapid response to face the current biodiversity crisis.
For this project there isn’t much of a problem to solve but an opportunity to improve. Improve
upon the project that was left which tried to choose the appropriate architecture, build a
completely new dataset and figure out what are the best parameters in order to achieve
certain goals.
SubjectsNeural networks (Computer science), Machine learning, Video recording, Xarxes neuronals (Informàtica), Aprenentatge automàtic, Vídeo
DegreeGRAU EN ENGINYERIA INFORMÀTICA (Pla 2010)
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