Having effective methods to access the images with desired object is essential nowadays with the availability of huge amount of digital images. We propose a semantic higher-level ...
Ismail Elsayad, Jean Martinet, Thierry Urruty, Cha...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the ...
We present a technique for local image representation that is invariant to viewpoint for scenes with arbitrary non-planar shape. We show that generic viewpoint invariance can be a...
In this paper, a novel personalized feature combination scheme is proposed for face verification. ANFIS (Adaptive Neuro-Fuzzy Inference System) and SVM (Support Vector Machine) ar...