BarkNet 1.0 (Part 2 of 4)

Published: 20 September 2019| Version 1 | DOI: 10.17632/xps2rnk8zp.1
, Philippe Giguère,


(Part 2 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.



Forestry, Agriculture Industry, Deep Learning