used an artificial neural network and canonical discriminant analysis to classify three species of amaranth (Amaranthus spp.) via 13 morphological features; and the overall accuracies were 80.7 and 74.8%, respectively [39]. Yasmin et al. distinguished healthy tomato seeds from infected seeds or ...
Those pictures have been reorganized by plant, and are listed below in six groups: Edible (134 plants) Amaranth[Amarantus retroflexus] American Elm[Ulmus americana] Aniseroot (Sweet cicely)[Osmorhiza longistylis] Apple[Malus] Arrowroot[Maranta arundinaceae] ...
This systematic literature review aims to present an in-depth investigation of the application of AI in supporting the management of weeds, plant nutrition, water, pests, and diseases. This systematic review was conducted using the PRISMA methodology and guidelines. Data from different papers ...
However, the accurate identification of plant seedlings is affected by the complex background environment such as light changes, weather, weeds, and terrain [2,3,4]. As an important data source for precision agriculture, drone remote sensing images can be used to protect crops, measure the ...