Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
Abstract Text documents usually embody visually oriented meta-information in the form of complex visual structures, such as tables. The semantics involved in such objects result in...
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial pr...
M. Emre Celebi, Y. Alp Aslandogan, Paul R. Bergstr...