We investigate a biologically motivated approach to fast visual classification, directly inspired by the recent work [13]. Specifically, trading-off biological accuracy for comput...
This paper proposes robust algorithms to deconvolve discrete noised signals and images. The solutions are derived as linear combinations of spline wavelet packets that minimize so...
Amir Averbuch, Valery A. Zheludev, Pekka Neittaanm...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
This paper presents a unified framework for object detection,
segmentation, and classification using regions. Region
features are appealing in this context because: (1) they enco...
Chunhui Gu, Joseph J. Lim, Pablo Arbelaez, Jitendr...
City environments often lack textured areas, contain
repetitive structures, strong lighting changes and therefore
are very difficult for standard 3D modeling pipelines.
We prese...