Improved YOLOv11 Framework with Channel Attention for High-Precision Identification of Luffa Leaf Diseases
Early accurate identification of luffa crop diseases is essential for timely treatment and high-quality agricultural production. Currently, luffa disease diagnosis relies solely on manual field inspection, which is labor-intensive and error-prone, and lacks assessment uniformity. While deep learning-based diagnostic me...