Title:	Automatic Coral Reef Annotation, Localization and Pixel-wise Parsing Using Mask R-CNN
Authors:	Soukup, Lukáš
Citation:	SOUKUP, L. Automatic Coral Reef Annotation, Localization and Pixel-wise Parsing Using Mask R-CNN. In Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum. Bucharest: CEUR-WS, 2021. s. 1359-1364. ISBN: neuvedeno , ISSN: 1613-0073
Issue Date:	2021
Publisher:	CEUR-WS
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85113420229 http://hdl.handle.net/11025/47278
ISBN:	neuvedeno
ISSN:	1613-0073
Keywords in different language:	Object detection, Semantic segmentation, Neural networks, Deep learning, Machine learning, Coral reefs detection, Coral reefs segmentation
Abstract in different language:	This paper describes the methods that were used for annotation, localization and pixel-wise parsing of the coral reefs from underwater images. The proposed system achieved competitive results in the third edition of ImageCLEFcoral 2021 challenge. Specifically, in case of annotation and localization task achieved mean average precision with Intersection over Union (IoU) greater that 0.5 (mAP@0.5) 0.121 and in case of pixel-wise parsing task achieved mAP@0.5 0.075 on the test set. The proposed method is based on Mask R-CNN object detection and segmentation framework with online data augmentations.
Rights:	© authors
Appears in Collections:	Konferenční příspěvky / Conference Papers (KKY) OBD

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