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Classification Algorithm for Person Identification and Gesture Recognition Based on Hand Gestures with Small Training Sets
2020
Sensors
Classification algorithms require training data initially labelled by classes to build a model and then to be able to classify the new data. The amount and diversity of training data affect the classification quality and usually the larger the training set, the better the accuracy of classification. In many applications only small amounts of training data are available. This article presents a new time series classification algorithm for problems with small training sets. The algorithm was
doi:10.3390/s20247279
pmid:33353008
pmcid:PMC7766068
fatcat:hrrjbpk6cbd33cb6hiupzgxi6m