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Tecniospring | Klemen Istenic | ACCIÓ

UW vision and Robotics

Deep Learning for Improved Ocean Map Reasoning

Project reference:  TECSPR18-1-0072
IP: Klemen Istenic and Rafael Garcia
TOTAL BUDGET : 113 391,82 €
DURATION: 01/09/2019 – 31/08/2021

With this project we want to explore and apply state-of-the-art DL methods towards devising robust and effective techniques to interpret scenes with high reliability. Building upon the 3D reconstruction system developed at ViCOROB, a distinctive departure of this research plan with respect to the state-of-the-art is the utilization of texture, shape outlines and 3D relief information in the context of benthic classification. Furthermore, high repurposability of trained models to other classification objectives yields a potentially high technological impact with multiple industrial applications (ranging from the oil and gas industry to environmental monitoring).

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