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Publication Type : Book Chapter
Publisher : Springer, Singapore
Source : In: Karuppusamy P., Perikos I., García Márquez F.P. (eds) Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol 243. Springer, Singapore. https://doi.org/10.1007/978-981-16-3675-2_48
Url : https://link.springer.com/chapter/10.1007/978-981-16-3675-2_48
Campus : Kochi
School : School of Computing
Department : Computer Science
Year : 2021
Abstract : Effective plant differentiation plays a vital role in agriculture, wherein this includes identifying crops and weeds in the farmland. The common method used for weed control is herbicides. However, the excessive use of herbicides will result in herbicides-resistance in weeds. An effective plant differentiation can decrease the expense of agriculture and increase crop quality, yield, and weed control. Henceforth, this research work has proposed a deep learning-based convolutional neural network to efficiently classify the plant leaves of three crops like canola, corn, and radish. In the experiment, the dataset used here is “bccr-segset,” which includes four categories like background, radish, corn, and canola. The dataset contains 30,000 images of these subclasses in four different growth stages.
Cite this Research Publication : Ashok A., Devadeth M.S., Vimina E.R. (October 2021) "Effective Plant Discrimination Using Deep Learning". In: Karuppusamy P., Perikos I., García Márquez F.P. (eds) Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol 243. Springer, Singapore. https://doi.org/10.1007/978-981-16-3675-2_48