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Blind image quality assessment (BIQA) methods aim to estimate the quality of a given test image without referring to the corresponding reference (original) image. Most BIQA methods use visual sensitivity models, which take into consideration intrinsic image characteristics (e.g. contrast, luminance, and texture) to identify degradations and estimate quality. For example, texture-based BIQA methods...
The amount of data produced every day on the internet increases every day and with the increasing popularity of the social networks the number of published photos are huge, and those pictures contain several implicit or explicit brand logos. Detecting this logos in natural images can provide information about how widespread is a brand, discover unwanted copyright distribution, analyze marketing campaigns,...
Facial expression recognition is a very important research field to understand human emotions. Many facial expression recognition systems have been proposed in the literature over the years. Some of these methods use neural network approaches with deep architectures to address the problem. Although it seems that the facial expression recognition problem has been solved, there is a large difference...
Multi-objective optimization plays an important role when one has fitness functions that are somehow conflicting with each other. Also, parameter-dependent machine learning techniques can benefit from such optimization tools. In this paper, we propose a multi-objective-based strategy approach to build compact though representative training sets for Optimum-Path Forest (OPF) learning purposes. Although...
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