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In discriminative tracking algorithms, the accuracy of classifier which relies heavily on the selection of training samples can directly influence the performance of visual tracking. Motivated by above, a tracking algorithm is presented based on regularized approximate residual weighted subsampling in the paper. Through the subsampling procedure, the corrupted samples which exert adverse impacts on...
Haze and mist always affect the quality of vision. If an image is suffered from haze or mist, then the object is unclear and the image seems whiter than the original one. There are several haze removal algorithms that can reduce the effect of haze and mist. However, if an image is not suffered from the haze and mist, applying the haze removal algorithm may darken the image. Therefore, in computer...
Multiple-Instance learning (MIL), which relaxes training annotation granularity from instance level to instance collection (bag) level by applying bag concept, obtains increasing attentions from computer vision community. Due to its flexible annotation mechanism, MIL has been naturally utilized on a variety of computer vision problems. And numerous models have been proposed, each of which is ingeniously...
On the basis of some research work about the educational evaluation index system of electronic games,we establish an educational evaluation system for electronic games using BP neural network model.The system has self-learning and adaptive characteristics.After the BP neural network trained with the expert knowledge,it not only has the experience of experts, but also realizes the changes from the...
The problem of ranking has recently gained attention in data learning. The goal ranking is to learn a real-valued ranking function that induces a ranking or ordering over an instance space. In this paper, we apply popular Bayesian techniques on ranking support vector machine. We propose a novel differentiable loss function called trigonometric loss function with the desirable characteristic of natural...
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