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Unsupervised Learning And Image Classification In High Performance Computing Cluster, Itauma Itauma
Unsupervised Learning And Image Classification In High Performance Computing Cluster, Itauma Itauma
Wayne State University Theses
Feature learning and object classification in machine learning have become very active research areas in recent decades. Identifying good features has various benefits for object classification in respect to reducing the computational cost and increasing the classification accuracy. In addition, many research studies have focused on the use of Graphics Processing Units (GPUs) to improve the training time for machine learning algorithms. In this study, the use of an alternative platform, called High Performance Computing Cluster (HPCC), to handle unsupervised feature learning, image and speech classification and improve the computational cost is proposed.
HPCC is a Big Data processing and …