1. Soil Texture Classification by Image: Deep Feature Learning vs. Handcrafted Methods for Precision Agriculture

Accurate soil texture classification is fundamental for precision agriculture, as it enables site-specific crop management that optimizes the utilization of agricultural resources and enhances overall crop productivity. This study presents a comparative analysis between features automatically extracted by a pre-trained SqueezeNet convolutional neural network (CNN) and three classical methods for manual feature extraction: Fast Fourier Transform (FFT), Gabor Filters, and Local Binary Patterns (LBP),... J.R. Favan , G.D. Faulin, F.M. Kasita Kashima, J. . Alegre, L.S. Gonçalves