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A new non-parametric method for reducing the number of dimensions in binary and continuous data, and for measuring the complexity of binary and continuous datasets, is introduced. The method, named Structural Manifold Analysis (SMA), is based on “Generalized Invariance Structure Theory” [1–6], a theory that has been successful in characterizing and accurately predicting human concept learning and...
Loop closure detection benefits simultaneous localization and mapping (SLAM) in building a consistent map of the environment by reducing the accumulate error. Handcrafted features have been successfully used in traditional approaches, whereas in this paper, we show that unsupervised features extracted by deep learning models, can improves the accuracy of loop closure detection. In particular, we employ...
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