Conference paper
Edge guided single depth image super resolution
Jun Xie, Rogerio Schmidt Feris, et al.
ICIP 2014
This paper presents a new probabilistic approach to document retrieval based on the assumption that, a Markov process can explain the process by which humans rank the relevance of do cuments to queries. The model ranks documents for retrieval based on their probability of r elevane. Two truining methods are presented. The model is compared with Latent Semantic Analysis (LSA) on two publicly available databases. The results show that, the new algorithm achieves Precision/Recall performance equivalent to or better than LSA.
Jun Xie, Rogerio Schmidt Feris, et al.
ICIP 2014
Eugene H. Ratzlaff
ICDAR 2001
Ritendra Datta, Jianying Hu, et al.
ICPR 2008
Jonathan H. Connell, Nalini K. Ratha, et al.
ICIP 2002