TITLE:
Classifying 3 Moss Species by Deep Learning, Using the “Chopped Picture” Method
AUTHORS:
Takeshi Ise, Mari Minagawa, Masanori Onishi
KEYWORDS:
Remote Sensing, Classification, Deep Learning, Object Identification
JOURNAL NAME:
Open Journal of Ecology,
Vol.8 No.3,
March
20,
2018
ABSTRACT: Especially
in recent years, deep learning has become a very effective tool for object
identification. However, in general, the automatic object identification tends
not to work well on ambiguous, amorphous objects such as vegetation. In this
study, we developed a simple but effective approach to identify ambiguous
objects and applied the method to several moss species. The technique called
chopped picture method, where teacher images are systematically dissected into
numerous small squares. As a result, the model correctly classified 3 moss
species and “non-moss” objects in test images with accuracy more than 90%.
Using this approach will help progress in computer vision studies for various
ambiguous objects.