Publications by authors named "Shafiun Miraz"

Plant diseases significantly impact crop productivity and quality, posing a serious threat to global agriculture. The process of identifying and categorizing these diseases is often time-consuming and prone to errors. This research addresses this issue by employing a convolutional neural network and support vector machine (CNN-SVM) hybrid model to classify diseases in four economically important crops: strawberries, peaches, cherries, and soybeans.

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Synopsis of recent research by authors named "Shafiun Miraz"

  • - Shafiun Miraz's recent research focuses on utilizing artificial intelligence, specifically a hybrid model combining convolutional neural networks (CNN) and support vector machines (SVM), to effectively detect and classify crop diseases that threaten agricultural productivity.
  • - The study specifically targets four economically important crops: strawberries, peaches, cherries, and soybeans, which are crucial for global agriculture.
  • - By implementing this lightweight CNN-SVM model, the research aims to enhance the accuracy and efficiency of disease identification, while also providing explainable AI visualizations to aid understanding and application in agricultural practices.