Learning and intelligence can happen everywhere, a case study: learning via Non-uniform 1D rulers with applications in image classification and recognition

Abstract

In this paper, we presented a non-uniform 1D ruler model and applied it in various image classification and image recognition scenarios, and some are for military technology usage. Our model is very simple, elegant and original, which is solved by convex quadratic programming. It has wide applications in pattern recognition and intelligent multimedia data analysis. We believe that a new research topic, namely, numeric calibration, has started, which is parallel to dimensionality reduction, feature selection, or metric learning etc. Our methods can be used as a pre-processing step for metric learning methods, in which, our learned calibrated feature space is used as input for them. The various combinations of our methods and metric learning methods, may lead to new interesting research problems.