We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...
Abstract. We propose a new generative model, and a new image similarity kernel based on a linked hierarchy of probabilistic segmentations. The model is used to efficiently segment ...
Abstract. A common practice to gain invariant features in object recognition models is to aggregate multiple low-level features over a small neighborhood. However, the differences ...
We present a biologically-motivated system for the recognition of actions from video sequences. The approach builds on recent work on object recognition based on hierarchical feed...
Hueihan Jhuang, Thomas Serre, Lior Wolf, Tomaso Po...
This paper presents a genetic programming based approach for optimizing the feature extraction step of a handwritten character recognizer. This recognizer uses a simple multilayer ...