@Article{cmc.2020.08857,
AUTHOR = {M. Vilasini, P. Ramamoorthy},
TITLE = {CNN Approaches for Classification of Indian Leaf Species Using Smartphones},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {3},
PAGES = {1445--1472},
URL = {http://www.techscience.com/cmc/v62n3/38365},
ISSN = {1546-2226},
ABSTRACT = {Leaf species identification leads to multitude of societal applications. There is 
enormous research in the lines of plant identification using pattern recognition. With the 
help of robust algorithms for leaf identification, rural medicine has the potential to 
reappear as like the previous decades. This paper discusses CNN based approaches for 
Indian leaf species identification from white background using smartphones. Variations 
of CNN models over the features like traditional shape, texture, color and venation apart 
from the other miniature features of uniformity of edge patterns, leaf tip, margin and 
other statistical features are explored for efficient leaf classification.},
DOI = {10.32604/cmc.2020.08857}
}