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Machine vision systems are being increasingly used for sophisticated applications such as classification and process control.
Some core technologies are needed to solve the problem in big data such as classification technology.
Kernel methods have become an increasingly popular tool for machine learning tasks such as classification, regression or novelty detection.
Deep learning has emerged as a powerful technique for any tasks related to machine learning such as classification and regression.
Wavelet-networks have been used successfully in various engineering applications such as classification, identification and control problems.
This strategy allows to cojointly optimize the classifier weights, architecture, and user-defined hyperparameters such as classification rate is maximized.
Many modern applications in fact, also require this formulation such as classification of protein functions and semantic scenes [26].
This involves data mining methods such as "classification," "clustering," or network analysis to identify "patterns of interest" [75 77].
Advanced data mining techniques such as classification can help in the early prediction of this disease and reduce its incidence and associated costs.
This represents the highest achievable accuracy using the remote sensing raster grid, where other factors influencing classification such as classification algorithm, radiometric calibration and sensor characteristics are excluded.
Metrics such as classification error rate, latency of the classification strategy and classification accuracy deterioration were assessed to estimate the scope of the CS-IBC as binary classifier.
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