Automatic feature descriptor in agriculture images using neural networks
Software that recognizes user-defined objects in aerial images for agriculture and derives quantitative estimators for plant count (N), green area index (GAI), growth stage (GS), deficient leaf area fraction (DLAF), and weeds area fraction (WAF), and potentially further measures. It employs a pre-trained multi-layer neural network model to classify regions of an image. The network is trained based on good examples of distinct types of objects that are provided by experts in aerial photography for agriculture. Afterwards, any provided aerial image or video can be analyzed with the pretrained software trained once.