We introduce a new metaphor for learning spatial relations--the 3D puzzle. With this metaphor users learn spatial relations by assembling a geometric model themselves. For this pu...
Bernhard Preim, Felix Ritter, Oliver Deussen, Thom...
—Current fully autonomous robots are unable to navigate effectively in visually complex environments due to limitations in sensing and cognition. Full teleoperation using current...
John Carff, Matthew Johnson, Eman El-Sheikh, Jerry...
Structured Hidden Markov Model (S-HMM) is a variant of Hierarchical Hidden Markov Model that shows interesting capabilities of extracting knowledge from symbolic sequences. In fact...
A new general framework for shape extraction is presented, based on the paradigm of water flow. The mechanism embodies the fluidity of water and hence can detect complex shapes. A ...
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...