Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed implementations of different versions of LDA, suitable ...
Sergio Valcarcel Macua, Pavle Belanovic, Santiago ...
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
In this paper, we propose two FPGA-area allocation algorithms based on profiling results for reducing the impact on performance of dynamic reconfiguration overheads. The problem o...
Elena Moscu Panainte, Koen Bertels, Stamatis Vassi...
Linear Discriminant Analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition....
Recently, i-vector extraction and Probabilistic Linear Discriminant Analysis (PLDA) have proven to provide state-of-the-art speaker verification performance. In this paper, the s...