We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We int...
In this work we present the Subsequence Similarity Language Model (S2-LM) which is a new approach to language modeling based on string similarity. As a language model, S2-LM gener...
This paper proposes a novel descriptor, granularitytunable
gradients partition (GGP), for human detection.
The concept granularity is used to define the spatial and angular
unce...
Yazhou Liu (Harbin Institute of Technology), Shigu...
Object detection in cluttered, natural scenes has a high
complexity since many local observations compete for object
hypotheses. Voting methods provide an efficient solution
to ...