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On Interpretable Approaches to Cluster, Classify and Represent Multi-Subspace Data via Minimum Lossy Coding Length based on Rate-Distortion Theory
To cluster, classify and represent are three fundamental objectives of learning from high-dimensional data with intrinsic structure.
Evaluation and Comparison of Deep Learning Methods for Pavement Crack Identification with Visual Images
Compared with contact detection techniques, pavement crack identification with visual images via deep learning algorithms has the advantages of not being limited by the material of object to be detected, fast speed and low cost.
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