DEEP LEARNING FOR EXPLORING ULTRA-THIN FERROELECTRICS WITH HIGHLY IMPROVED SENSITIVITY OF PIEZORESPONSE FORCE MICROSCOPY

Deep learning for exploring ultra-thin ferroelectrics with highly improved sensitivity of piezoresponse force microscopy

Abstract Hafnium oxide-based ferroelectrics have been extensively studied because of their existing ferroelectricity, even in ultra-thin film form.However, studying the weak response from ultra-thin film requires improved measurement sensitivity.In general, resonance-enhanced piezoresponse force microscopy (PFM) has been used to characterize ferroe

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Seasonal variations of physicochemical characteristics of brewery industry effluent and receiving water of Ikpoba-Oha Rivers, Benin City, Nigeria

The impact of the effluents from a Brewery industry on the water quality of Ikpoba-Oha River was carried out during wet and dry seasons, 2016.Water samples from three selected points in the river were analyzed for pH, temperature, total solids, total dissolved solids, Hardness, BOD, COD, DO, Chlorides, phosphates, Hand Sanitizer sulphates.Samples w

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A Multilayer Fusion Light-Head Detector for SAR Ship Detection

Synthetic aperture radar (SAR) ship detection is a heated and challenging problem.Traditional methods are based on hand-crafted feature extraction or limited shallow-learning features representation.Recently, with the excellent ability of feature representation, deep neural networks such as faster region based convolution neural network (FRCN) have

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