Gradient and Log-based Active Learning for Semantic Segmentation of Crop and Weed for Agricultural Robots
Rasha Sheikh,Andres Milioto,Philipp Lottes,Cyrill Stachniss,Maren Bennewitz,Thomas Schultz,Rasha Sheikh,Andres Milioto,Philipp Lottes,Cyrill Stachniss,Maren Bennewitz,Thomas Schultz
Annotated datasets are essential for supervised learning. However, annotating large datasets is a tedious and time-intensive task. This paper addresses active learning in the context of semantic segmentation with the goal of reducing the human labeling effort. Our application is agricultural robotics and we focus on the task of distinguishing between crop and weed plants from image data. A key cha...
