In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
The performance of traditional image retrieval approaches remains unsatisfactory, as they are restricted by the wellknown semantic gap and the diversity of textual semantics. To t...
Chuanghua Gui, Jing Liu, Changsheng Xu, Hanqing Lu
We propose structured models for image labeling that take into account the dependencies among the image labels explicitly. These models are more expressive than independent label ...
This paper describes a face detection approach via learning local features. The key idea is that local features, being manifested by a collection of pixels in a local region, are ...
Xiangrong Chen, Lie Gu, Stan Z. Li, HongJiang Zhan...
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...