Detecting diseases in apple tree leaves using FPN-ISResNet-Faster RCNN

• Published in: European journal of remote sensing Vol. 56; no. 1
• Main Authors: Hou, Jingwei, Yang, Chen, He, Yonghong, Hou, Bo
• Format: Journal Article
• Language: English
• Published: Cagiari Taylor & Francis 31.12.2023; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Accuracy; Apple leaf disease; Apples; Artificial neural networks; convolutional neural network; Crop diseases; Datasets; Deep learning; Engineering; Environmental engineering; Faster RCNN; Feature extraction; FPN; Fruit trees; Fruits; ISResNet; Leaves; Machine learning; Neural networks; Plant diseases

Apple leaf diseases typified by small disease spots are generally difficult to detect in images. This study proposes a deep learning model called the feature pyramid networks (FPNs) -inception squeeze-and-excitation ResNet (ISResNet)-Faster RCNN (region with convolutional neural network) model to im...