The leaf is one of the plant organs, contains chlorophyll, and functions as a catcher of energy from sunlight which is used for photosynthesis. Perfect leaves are composed of three parts, namely midrib, stalk, and leaf blade. The way to identify the type of plant is to look at the shape of the leaf edges. The shape, color, and texture of a plant's leaf margins may influence its leaf veins, which in this vein morphology carry information useful for plant classification when shape, color, and texture are not noticeable. Humans, on the other hand, may fail to recognize this feature because they prefer to see plants solely based on leaf form rather than leaf margins and veins. This research uses the Wavelet method to denoise existing images in the dataset and the Convolutional Neural Network classifies through images. The results obtained using the Wavelet Convolutional Neural Network method are equal to 97.13%. 

Dewi, W., & Utomo, W. H. (2021). Plant classification based on leaf edges and leaf morphological veins using wavelet convolutional neural network. Applied Computer Science, 17(1), 81-89. https://doi.org/10.23743/acs-2021-08

Dewi, Wulan, and Wiranto Herry Utomo. "Plant classification based on leaf edges and leaf morphological veins using wavelet convolutional neural network." Applied Computer Science 17, no. 1 (2021): 81-89.

W. Dewi, and W. H. Utomo, "Plant classification based on leaf edges and leaf morphological veins using wavelet convolutional neural network," Applied Computer Science, vol. 17, no. 1, pp. 81-89, 2021, doi: 10.23743/acs-2021-08.

Dewi W, Utomo WH. Plant classification based on leaf edges and leaf morphological veins using wavelet convolutional neural network. Applied Computer Science. 2021;17(1):81-89.