In this paper, we present multiple novel applications for local intrinsic dimension estimation. There has been much work done on estimating the global dimension of a data set, typi...
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
We have proposed a complete system for text detection and localization in gray scale scene images. A boosting framework integrating feature and weak classifier selection based on...
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
This paper presents a new algorithm for enhancing the efficiency of simulation-based optimisation using local search and neural network metamodels. The local search strategy is ba...