ROOT IDENTIFICATION WITH MULTIPLE INSTANCE LEARNING PUBLISHED IN MACHINE VISION AND APPLICATIONS!

Congratulations to our labmates and collaborators Guohao Yu, Alina Zare, Hudanyun Sheng, Roser Matamala, Joel Reyes-Cabrera, Felix Fritschi and Thomas Juenger! Their paper, “Root Identification in Minirhizotron Imagery with Multiple Instance Learning”, was recently published in Machine Vision and Applications!

Their paper explores the use of multiple instance learning to segment minirhizotron images of plant roots.  Contrary to traditional methods which require precisely-labeled groundtruth, their work utilizes weak annotations, saving both time and burden.  Check out the paper and code here!