Deep features from Pre-trained CNNs and a vision transformer for amazonian timber species recognition using classical machine learning and random image patches
Accurate identification of timber species is essential for biodiversity conservation, sustainable forest management, and timber supply chain control. This study evaluated four pre-trained convolutional neural networks—ResNet50, VGG16, InceptionV3, and MobileNetV2 and a Vision Transformer (ViT) as fixed feature extrac...