BarkNet 1.0 (Part 3 of 4)
Published: 20 September 2019| Version 1 | DOI: 10.17632/553g3v244g.1
Contributors:
Philippe Giguère, , Description
(Part 3 out of 4) 23,000 cropped images of tree bark, for 23 species of trees around Quebec City, Canada. The images were captured at a distance between 20-60 cm away from the trunk. Labels include: individual tree ID, its species, and its DBH (diameter at breast height). Pictures were taken with four different devices: Nexus 5, Samsung Galaxy S5, Samsung Galaxy S7, and a Panasonic Lumix DMC-TS5 camera. The dataset is sufficiently large to train a Deep network such as ResNet for species recognition.
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Institutions
Universite Laval
Categories
Forestry, Agriculture Industry, Deep Learning