Whale counting in satellite and aerial images with deep learning.

ABSTRACT: Despite their interest and threat status, the number of whales in world's oceans remains highly uncertain. Whales detection is normally carried out from costly sighting surveys, acoustic surveys or through high-resolution images. Since deep convolutional neural networks (CNNs) are achieving great performance in several computer vision tasks, here we propose a robust and generalizable CNN-based system for automatically detecting and counting whales in satellite and aerial images based on open data and tools. In particular, we designed a two-step whale counting approach, where the first CNN finds the input images with whale presence, and the second CNN locates and counts each whale in those images. A test of the system on Google Earth images in ten global whale-watching hotspots achieved a p

SUBMITTER: Guirado E 

PROVIDER: S-EPMC6776647 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature