residential location choice modeling is one of the areas in transportation planning that attempts to examine households location search behavior incorporating their trade-offs between housing quality, prices or rents, distance to work and other key factors. this brings up the need to come up with methods to logically allocate credible choice alternatives for individuals.this article attempts to...

in this paper, different input-oriented ratio-based dea (dea-r-i) models are proposed. by presenting the envelopment-additive-enhanced russell model based on the dea-r-i form, each decision making unit is evaluated and its efficiency score is calculated. also, by presenting the central resource allocation model based on the dea-r-i form, a suitable benchmark for all dmus is proposed by solving ...

This paper presents a system of data decomposition and spatial mixture modeling for part based models. Recently, many enhanced part based models (with e.g., multiple features, more components or parts) have been proposed. Nevertheless, those enhanced models bring high computation cost together with the risk of over-fitting. To tackle this problem, we propose a data decomposition method for part...

  In this paper, different input-oriented ratio-based DEA (DEA-R-I) models are proposed. By presenting the envelopment-additive-enhanced Russell model based on the DEA-R-I form, each decision making unit is evaluated and its efficiency score is calculated. Also, by presenting the central resource allocation model based on the DEA-R-I form, a suitable benchmark for all DMUs is proposed by solvin...

Automated object detection is perhaps the most central task of computer vision and arguably the most difficult one. This paper extends previous work on part-based models by using accurate geometric models both in the learning phase and at detection. In the learning phase manual annotations are used to reduce perspective distortion before learning the part-based models. That training is performe...