EF-CenterNet: An efficient anchor-free model for UAV-based banana leaf disease detection

Abstract

UAV-based remote sensing combined with deep neural networks has recently emerged for automated leaf disease detection on large-scale farmland. This research focuses on designing a fast and high-precision model for detecting banana leaf diseases from UAV-based samples in real-field conditions, where disease-affected regions are dense with different sizes. In detail, we propose a lightweight yet efficient banana leaf disease detection model with an anchor-free design, Efficient Feature CenterNet (EF-CenterNet). To effectively handle dense scenarios, our model employs the EfficientViT block, built based on the depth-wise separable convolutional layer, incorporated with the modified ReLU-attention mechanism. Feature Pyramid Network is then involved in tackling the size variation of contaminated regions via top-down upsampling architecture to fuse the feature in multi-scale levels. The proposed model …