CNN Approaches for Classification of Indian Leaf Species Using Smartphones

被引:14
作者
Vilasini, M. [1 ]
Ramamoorthy, P. [2 ]
机构
[1] Kra Inst Engn & Technol, Coimbatore 641407, Tamil Nadu, India
[2] Adithiya Inst Engn & Technol, Coimbatore 641107, Tamil Nadu, India
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2020年 / 62卷 / 03期
关键词
Deep learning; CNN; classification; transfer learning; prewitt edge detection; SUPPORT VECTOR MACHINE; IMAGE TEXTURE; EDGE-DETECTION; RECOGNITION; SEGMENTATION; IDENTIFICATION; VEGETATION; FEATURES; PATTERN; SYSTEM;
D O I
10.32604/cmc.2020.08857
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1445 / 1472
页数:28
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