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The performance of most of the classification models is dependent on the data used for training. The data must be reliable, robust and meticulously labelled. In order to form such a data a systematical approach has been designed and moreover, it should be. The data set was collected from a well-known source, namely Center for Language Engineering available at http://www.cle.org.pk.

Occlusion, glare and secondary reflections formed due to and on the spectacles - results in poor detection, localization, and recognition of eye/face features. We term all the problems related to the usage of spectacles as The spectacle problem. Though several studies on the spectacle detection and removal have been reported in the literature, the study focusing on spectacle problem removal is very limited. One of the main reasons being, the nonavailability of a facial image database highlighting the spectacle problems.

Stereolithographic files of three different mesh designs; Square, Triangular and Hexagonal (top to bottom rows in image). Each mesh design is provided in three different deformations; Flat/no deformation, Mode 1 deformation and Mode 5 deformation (left to right columns in image). Mode 1 and Mode 5 deformation was obtained by modal study with the four outer surfaces of the frame fixed. Note that the out-of-plane deformation has been scaled to better proportions.

High energy consumption is a challenging issue that an ever increasing number of mobile applications face today.
However, energy consumption is being tested in an ad hoc way, despite being an important non-functional requirement of an application.
Such limitation becomes particularly disconcerting during software testing: on the one hand, developers do not really know how to measure energy; on the other hand, there is no knowledge as to what is the energy overhead imposed by the testing framework.