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Recent progress in big data and computer vision with deep learning models has gained a lot of attention. Deep learning has been performed on tasks such as image classification, object detection, image segmentation, image captioning, visual question and answering, using large collections of annotated images. This calls for more curated large image datasets with clearer descriptions, cleaner contents,...
DBSCAN is a well-known clustering algorithmwhich is based on density and is able to identify arbitraryshaped clusters and eliminate noise data. However, parallelization of DBSCAN is a challenging work because based on MPIor OpenMP environments, there exist the issues of lack of fault-tolerance and there is no guarantee that workload is balanced. Moreover, programming with MPI requires data scientists...
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