000			01377nam a22001457a 4500
008			221213b ||||| |||| 00| 0 eng d
100			_aBELLO ABRAHAM ITEOLUWAKISI _99777
245			_aMACHINE LEARNING-BASED DECISION SUPPORT FOR DETECTING MAIZE PLANT DISEASE
250			_aDr Deborah D. Aleburu
260			_aMountain Top University _bComputer Science _c2022
300			_axi;'54p.
520			_aMaize is an essential crop for us humans, it can be both used in the manufacturing industry and also for foods, etc. The goal of this project is to develop a machine learning-based decision support system for detecting maize plant disease. In order to achieve this, it was necessary to analyse and review machine learning techniques and algorithms best for detecting maize disease. Google colab was used to build the model to detect the disease. The model was built to reduce cost and time of detecting maize plant disease. The model employs a convolutional neural network to identify specific diseases in maize and was able to get a satisfactory result. The model was able to accurately detect the disease, this improves the rate at which maize crop loss can be reduced due to infections or diseases which have infected the plants. Keywords: Machine learning (ML), Decision support system, Convolutional Neural Network (CNN)
650			_aComputer Science _91105
942			_cTHS
999			_c7115 _d7115