Research Tools: InsectNet Technology Identifies Insects Around the World and Around the Farm

From Iowa State University:

A farmer notices an unfamiliar insect on a leaf.

Is this a pollinator? Or a pest? Good news at harvest time? Or bad? Need to be controlled? Or not?

That farmer can snap a picture, use a smartphone or computer to feed the photo into a web-based application called InsectNet and, with the help of machine learning technology, get back real-time information.

“The app identifies the insect and returns a prediction of its taxonomic classification and role in the ecosystem as a pest, predator, pollinator, parasitoid, decomposer, herbivore, indicator and invasive species,” said a scientific paper describing InsectNet recently published by the journal PNAS Nexus. Iowa State University’s Baskar Ganapathysubramanian and Arti Singh are the corresponding authors. (See sidebar for a complete list of authors.)

InsectNet – which is backed by a dataset of 12 million insect images, including many collected by citizen-scientists – provides identification and predictions for more than 2,500 insect species at more than 96 percent accuracy. When the application isn’t sure about an insect, it says it is uncertain, giving users more c

You can’t go to an app store and download a version just yet, said [Baskar] Ganapathysubramanian, the Joseph and Elizabeth Anderlik Professor in Engineering and director of the AI Institute for Resilient Agriculture based at Iowa State.

Learn More, Read the Complete Announcement

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Hat Tip: RB

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