Deep Neural Networks for Marine Debris Detection in Sonar Images

Garbage and waste disposal is one of the biggest challenges currently faced by
mankind. Proper waste disposal and recycling is a must in any sustainable
community, and in many coastal areas there is significant water pollution in the form of floating or submerged garbage. This is called marine debris. There is interest in recovering this kind of debris as general cleanup of water bodies, and an automated way is preferable.
Encouraged by the advances in Computer Vision from the use Deep Learning, we
propose the use of Deep Neural Networks (DNNs) to detect marine debris in the
bottom of water bodies (seafloor, lake and river beds) from sonar images. This
talk, based on my ongoing PhD thesis, covers a comprehensive evaluation of the use of DNNs for the problem of marine debris detection, including image classification, detection proposals, end-to-end detection and recognition as well as matching in sonar images.


Raum A 1.03, Robert-Hooke-Str. 1 in Bremen

In der Regel sind die Vorträge Teil von Lehrveranstaltungsreihen der Universität Bremen und nicht frei zugänglich. Bei Interesse wird um Rücksprache mit dem Sekretariat unter sek-ric(at)dfki.de gebeten.

zuletzt geändert am 31.03.2023
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