We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
We introduce the novel problem of inter-robot transfer learning for perceptual classification of objects, where multiple heterogeneous robots communicate and transfer learned obje...
Some supervised-learning algorithms can make effective use of domain knowledge in addition to the input-output pairs commonly used in machine learning. However, formulating this a...
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
This work is designed to contribute to a deeper understanding of the recently proposed Merging SOM (MSOM). Its context model aims at the representation of sequences, an important s...