molecular) models of a species have been developed and demonstrated to be accurate, these models can be queried to determine which aspects of the observed patterns of variation and variation limits are being used to achieve the identification, thus opening the way for the discovery of new and (potentially) more reliable taxonomic characters. iNaturalist is a global citizen science project and social network of naturalists that incorporates both human and automatic identification of plants, animals, and other living creatures via browser or mobile apps. Pl@ntNet is a global citizen science project which provides an app and a website for plant identification through photographs, based on machine-learning Leaf Snap is an iOS app developed by the Smithsonian Institution that uses visual recognition software to identify North American tree species from photographs of leaves. Google Photos can automatically identify various species in photographs. Plant.id is a web application and API made by FlowerChecker company which uses a neural network trained on photos from FlowerChecker mobile app. See also Multi-access key References cited External links Here are some links to the home pages of species identification systems. The SPIDA and DAISY system are essentially generic and capable of classifying any image material presented. The ABIS and DrawWing''' system are restricted to insects with membranous wings as they operate by matching a specific set of characters based on wing venation. The SPIDA system ABIS DAISY DrawWing LeafSnap Pl@ntNet Species Automatic identification and data capture Comparative anatomy Bioinformatics Applications of computer vision