Abstract: Aided target detection in infrared data has proven an important area of investigation for both military and civilian applications. While target detection at the object or pixel-level has been explored extensively, existing approaches require precisely-annotated data which is often… Read More
Tag: class activation map
MIL-CAM ACCEPTED TO ECCV 2020 WORKSHOP ON COMPUTER VISION PROBLEMS IN PLANT PHENOTYPING!
Congratulations to our labmates and collaborators: Guohao Yu, Alina Zare, Weihuang Xu, Roser Matamala, Joel Reyes-Cabrera, Felix B. Fritschi and Thomas E. Juenger! Their paper, “Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM” was recently accepted to the 16th European Conference… Read More
WEAKLY SUPERVISED MINIRHIZOTRON IMAGE SEGMENTATION WITH MIL-CAM
Abstract: We present a multiple instance learning class activation map (MIL-CAM) approach for pixel-level minirhizotron image segmentation given weak image-level labels. Minirhizotrons are used to image plant roots in situ. Minirhizotron imagery is often composed of soil containing a few… Read More