Causality-inspired method boosts crop pest recognition

A team of researchers led by Professor Xie Chengjun and Associate Professor Zhang Jie at the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, have developed an innovative Decoupled Feature Learning (DFL) framework inspired by causal inference to address the challenge of distribution bias in crop pest recognition. A team of researchers led by Professor Xie Chengjun and Associate Professor Zhang Jie at the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, have developed an innovative Decoupled Feature Learning (DFL) framework inspired by causal inference to address the challenge of distribution bias in crop pest recognition. Plants & Animals Agriculture Phys.org – latest science and technology news stories