Categorization of Plant Sapling using Deep Learning
M.Kavitha1, Nithiesh Kumar N2, Lalith Kumar.V3, Mathan S4, Mohankumar M5
1Kavitha M, Assistant Professor at Sri Krishna College of Engineering and Technology, Coimbatore. Tamil Nadu, India.
2Nithiesh Kumar M is currently pursuing his Bachelor of Engineering in the stream of Computer Science at Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India.
3Lalith Kumar V, pursuing his Bachelor of Engineering in the stream of Computer Science at Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India.
4Mathan S, pursuing his Bachelor of Engineering in the stream of Computer Science at Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India.
5Mohankumar M, pursuing his Bachelor of Engineering in the stream of Computer Science at Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 289-292 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7569068519/2019©BEIESP | DOI: 10.35940/ijeat.E7569.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Digital Image Recognition, Weeds, Plants, Neural Network