Abstract. This paper presents a new multi-pass hierarchical stereo-matching approach for generation of digital terrain models (DTMs) from two overlapping aerial images. Our method ...
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
Two main issues arise when working in the area of texture segmentation: the need to describe the texture accurately by capturing its underlying structure, and the need to perform ...
We present a development environment for automatically building smart, security-aware GUIs following a model-based approach. Our environment consists of a number of plugins that h...
There are two main topics in this paper: (i) Vietnamese words are recognized and sentences are segmented into words by using probabilistic models; (ii) the optimum probabilistic mo...