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In this paper, we propose a multi-class boosting method (multiBoost.imb) to address difficulties of learning from imbalanced data set as well as employment of stable base learners. A random resampling strategy is incorporated to diversify the training data set and to recover balance among all classes. Extending AdaBoost by adding an error adjustment parameter, early termination in the training phase...
Even though facial expressions have universal meaning in communications, their appearances show a large amount of variation due to many factors, such as different image acquisition setups, different ages, genders, and cultural backgrounds etc. Collecting enough amounts of annotated samples for each target domain is impractical, this paper investigates the problem of facial expression recognition in...
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