Abstract
Typically, bell pepper growers are unaware of bacterial spot disease on their plants. As the condition progresses, the yield usually declines. Like a virus or wilt, pepper-related diseases will obliterate your entire garden. The best course of action when there are problems with the pepper crop is to remove the sick plant before it spreads to the rest of the garden. For the same purpose, we need to have a good identification model which can differentiate between a healthy image of the leaf and an unhealthy leaf. The method of processing digital data in the form of pixels is known as image processing. Due to the complexity of the data, plant disease identification is the main problem with image processing. In this study, we employed two deep learning models, AlexNet and VGG16, to identify leaf illnesses in bell pepper plants which show good accuracy of 97.80 and 99.38% respectively.
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The authors expressed their gratitude to the authorities of the National Institute of Technology, Hamirpur for providing necessary infrastructural facilities. They also extend their gratitude to their supervisor for guiding them.
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Kapoor, K., Singh, S., Singh, N.P., Priyanka (2023). Bell-Pepper Leaf Bacterial Spot Detection Using AlexNet and VGG-16. In: Senjyu, T., So-In, C., Joshi, A. (eds) Smart Trends in Computing and Communications. SmartCom 2023. Lecture Notes in Networks and Systems, vol 650. Springer, Singapore. https://doi.org/10.1007/978-981-99-0838-7_44
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