Title :
Leaf classification utilizing a convolutional neural network
Author :
Jassmann, Timothy J. ; Tashakkori, Rahman ; Parry, R. Mitchell
Author_Institution :
Dept. of Comput. Sci., Appalachian State Univ., Boone, NC, USA
Abstract :
Tree identification is an important task in biological research. Since not all biologists are qualified for this task and experts are not accessible all the time, an application to assist in plant identification would be extremely useful. This paper describes an application classifies the type of a tree based on a picture of one of its leaves. The system developed for this research utilizes a convolutional neural network in an android mobile application to classify natural images of leaves.
Keywords :
Android (operating system); biology computing; image classification; mobile computing; neural nets; vegetation; android mobile application; biological research; convolutional neural network; leaf classification; natural image classification; plant identification; tree identification; tree type classification; Accuracy; Biological neural networks; Convolution; Cost function; Covariance matrices; Training; convolutional neural network; image processing; leaf classification;
Conference_Titel :
SoutheastCon 2015
Conference_Location :
Fort Lauderdale, FL
DOI :
10.1109/SECON.2015.7132978
