Dynamic Aspect Oriented Programming (AOP) technologies typically provide coarse-grained mechanisms for adapting aspects that cross-cut a system deployment; i.e. whole aspect modules can be added and removed at runtime. However, in this paper we demonstrate that adaptation of the finer-grained elements of individual aspect modules is required in highly dynamic systems and applications. We presen...

Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task due to two main issues: lack of sufficient training data for every class and difficulty in learning discriminative features for representation. In this paper, to address the two issues, we propose a two-phase framework for recognizing images from unseen fine-grained classes, i.e. ...