Open AccessCategorization of Plant Sapling using Deep Learning
Author(s) -
Muthu Subash Kavitha,
NACHAPPAN K.M,
Lalit Kumar,
Santosh Mathan,
M. Mohankumar
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e7569.088619
Subject(s) - rgb color model , deep learning , convolutional neural network , artificial intelligence , categorization , computer science , agricultural engineering , machine learning , weed , artificial neural network , production (economics) , crop , seedling , deep neural networks , agronomy , engineering , biology , macroeconomics , economics
According to the latest research, the current increment of the food production will not be able to satisfy the market due to the lack of farmers, and land areas with limited resources. Weeds are grown along with the plant seedlings, The Amount of water and fertilizers needed for the plant seedlings, Crop placement, and row spacing, are being the Major problems. The usage of deep learning using digital image processing could be an efficient way to overcome these problems. Deep Learning is based on Data Representations, Artificial and Neural networks. Plant species can be recognized using RGB images especially in the problem of weed detection. The resources and the row spacing needed for the seedlings can be fulfilled by recognizing the image with the preloaded datasets of the seedling.