We propose a low cost method for the correction of the output of OCR engines through the use of human labor. The method employs an error estimator neural network that learns to as...
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Estimation of distribution algorithms (EDAs) that use marginal product model factorizations have been widely applied to a broad range of, mainly binary, optimization problems. In ...
Traffic patterns in manufacturing machines exhibit strong temporal correlations due to the underlying repetitive nature of their operations. A MAC protocol can potentially learn t...
Object detection in aerial imagery has been well studied in computer vision for years. However, given the complexity of large variations of the appearance of the object and the ba...