Image Based Plant Disease Classification Using Deep Learning Technique (International Journal of Innovative Research in Engineering & Management, 2023)
As living beings, our reliance on plants and  animals for sustenance is crucial. However, the available food  resources cannot sustain the global population for extended  periods, as only 29% of the Earth's land is suitable for  sustaining the entire ecosystem. If we didn't have plant-eating  bacteria or locusts, we might have enough resources to last  for years. This is where my project, Plant Disease Detection  and Recognition, comes into play. The main objective of this  project is to identify and diagnose the diseases affecting  plants, as well as determine the most effective treatments. By utilizing this system, we can obtain accurate information  about the specific diseases afflicting plants. Additionally, we  can identify the appropriate medications for eradicating these  diseases completely. Plant diseases pose significant threats to  the well-being of plants and trees, making it vital to detect  them early in order to take appropriate measures.  Understanding the type of disease before administering  treatment is crucial. With a 92% accuracy rate, our system  enables us to work on plants effectively, thereby extending  their lifespan. After undergoing multiple tests, this initiative has emerged as  a promising boon for humankind. Farmers, who serve as the  backbone of nations, play a crucial role in our survival.  Ensuring that they receive fair prices for their yields is  paramount, and our system will play a significant role in  achieving this. By supporting agricultural sustainability and  promoting healthier crops, we can create a positive impact on  food production and contribute to the overall well-being of  society.
Keywords: Plant diseases detection; CNN; image classification; deep learning in agriculture