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IMAGE: The input image (left) and the output image (right), processed by the fully convolutional neural network view more
Credit: Skoltech
Skoltech scientists have created a new monitoring system for agricultural applications that performs real-time image segmentation on board the drone to identify hogweed. The research was published in a high-profile journal,
IEEE Transactions on Computers.
Sosnovsky s hogweed is equally hazardous for farming, local ecosystems, and human health. Direct contact with human skin, especially if aggravated by exposure to the Sun, causes severe burns that require continuous medical care and take weeks to heal. The rampant spread of Sosnovsky s hogweed has become a real environmental disaster that extends across the whole of Russia, from its central part to Siberia and from Karelia to the Caucasus. Every year, the government allocates huge budgets (last year, 350 million rubles for Moscow alone) for hogweed elimination. Eradicating