Muhammad Khurram Shaikh

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Intermodality face matching or Heterogeneous face recognition involves matching faces from different modalities such as infrared images, sketch images and low/high resolution visual images. This problem is further alleviated due to inherit problems in face recognition such as pose, expression, illumination, occlusion etc. Existing face recognition(More)
Mutants of Bacillus amyloliquefaciens resistant to at least 10 micrograms/ml of tunicamycin were isolated and shown to be pleiotropic. The mutants were more resistant to streptomycin, chloramphenicol, kanamycin and neomycin than was the parent strain but less resistant to penicillin G and tetracycline. They were more autolytic, presumably due to an altered(More)
Anilogel-E, a cross-linked starch, can be used with distinct advantages where native starch or soluble starch are conventionally used, e.g. in scoring for amylolytic organisms, as an ingredient of fermentation media, and in enhancing protoplast regeneration. It is particularly useful for the direct visualization of amylase producing micro-organisms on solid(More)
Identifying the type of modalities of the query image which can be of types visual, NIR, digital camera, web camera etc. have been assumed to be available before face matching. This leads to a major drawback in achieving fully automated heterogeneous face recognition as real world scenarios cannot be reflected. Therefore, modality identification is an(More)
Heterogeneous face recognition is a challenging research problem which involves matching of the faces captured from different sensors. Very few methods have been designed to solve this problem using intensity features and considered small sample size issue. In this paper, we consider the worst case scenario when there exists a single instance of an(More)
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