Academic Research & Scholarly Contributions
This research presents an ensemble approach using multiple deep convolutional neural network architectures for accurate classification of human skin diseases. The proposed method demonstrates improved performance compared to individual models.
This study develops a mobile-compatible deep convolutional neural network model for efficient detection and classification of maize leaf diseases. The solution enables farmers to identify crop diseases using smartphone cameras for timely intervention.