Student Name: KL Dhlakama
About the student
Kamogelo Dhlakama here, an Honors student in Informatics with a flair for innovative problem-solving. My passion for AI and IT propels me towards envisioning a sustainable future through cutting-edge technologies. I'm dedicated to discovering boundary-pushing solutions that pave the way for a brighter tomorrow.
About the Project
This project's main aim is to develop a better system for spotting Common Rust disease in maize crops. This fungal disease affects maize yields, especially in areas like South Africa where maize is crucial for food and the economy. I use Convolutional Neural Networks (CNNs) for this. They're great at categorizing images, making them useful for identifying diseases like Common Rust in maize pictures. Here's a quick breakdown of the process: Data Collection: I gathered many pictures of healthy and diseased maize. These pictures are then edited for size, color, and consistency. Using CNNs: My system uses CNNs to spot signs of Common Rust in these images. The layers in the network pick out disease traits, making detection effective. Training & Testing: While training, I measure how close the system's predictions are to real labels, improving it step by step. I track accuracy and other performance indicators to see how well it's doing. User Interface: I made easy-to-use tools for farmers and experts to check maize images for disease in real-time. This automation speeds things up and lowers the chances of mistakes.
