A simple ensemble method for transfer learning-based cotton leaf disease detection using machine learning
The agricultural sector in South Asia, especially countries like Bangladesh, China, and India, relies heavily on cotton, a crop vital to both the economy and the global textile industry. However, cotton production faces significant challenges from leaf diseases, which can drastically reduce crop yield, impacting farmers’ livelihoods and the region’s economy. Traditional methods for detecting these diseases involve manual inspection, which is labor-intensive, time-consuming, and prone to error.