BOOSTING FRAUD DETECTION IN MOBILE PAYMENT WITH PRIOR KNOWLEDGE

Boosting Fraud Detection in Mobile Payment with Prior Knowledge

With the prevalence of mobile e-commerce, fraudulent transactions conducted by robots are becoming increasingly common in mobile payments, which is severely undermining market fairness and resulting in financial losses.It has become a difficult problem for mobile applications to identify robotic automation accurately and efficiently from a massive

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Integration of Convolutional Neural Networks and Object-Based Post-Classification Refinement for Land Use and Land Cover Mapping with Optical and SAR Data

Object-based image analysis (OBIA) has been widely used for land use and land cover (LULC) mapping using optical and synthetic aperture radar (SAR) images because it can utilize spatial information, reduce the effect of salt and pepper, and delineate LULC boundaries.With recent advances in machine learning, convolutional neural networks (CNNs) have

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