Existing semantic segmentation methods mostly rely on per-pixel supervision, unable to capture structural regularity present in natural images. Instead of learning to enforce semantic labels on individual pixels, we propose to enforce affinity field patterns in individual pixel neighbourhoods, i.e., the semantic label patterns of whether neighbouring pixels are in the same segment should match ...

This paper addresses the problem of mapping natural language to its semantics. It presupposes that the input is in random (compressed) form and proceeds to detail a methodology for extracting the semantics from that normal form. The idea is to enumerate contextual cues and learn to associate those cues with meaning. The process is inherently fuzzy and for this reason is also inherently adaptive...

Agricultural environment mapping is the premise of autonomous navigation agricultural robots. Due to undulating terrain and chaotic environment, it challenging accurately map environmental maize field using existing LOAM (LiDAR odometry mapping) methods. This paper proposes a method based on stalk semantic features for 6-DOF (degrees freedom) pose estimation with robots operating in dynamic env...