Titlebook: Extreme Learning Machines 2013: Algorithms and Applications; Fuchen Sun,Kar-Ann Toh,Kezhi Mao Book 2014 Springer International Publishing

TOXIC

Demographic Attributes Prediction Using Extreme Learning Machine,havior targeting. Although a variety of subjects are involved with demographic attributes prediction, e.g. there are requirements to recognize and predict demography from psychology, but the traditional approach is dynamic modeling on specified field and distinctive datasets. However, dynamic modeli

马笼头

亚当心理阴影

cacophony

Indoor Location Estimation Based on Local Magnetic Field via Hybrid Learning,measurements for a single location and the relative obvious difference in most of locations. Under this phenomenon, a hybrid learning method based on the local magnetic field measurements is proposed. (1) Kalman filter is firstly utilized to smooth the initial samples in order to obtain the stable d

Vsd168

A Novel Scene Based Robust Video Watermarking Scheme in DWT Domain Using Extreme Learning Machine,n using a newly developed SLFN commonly known as Extreme Learning Machine (ELM). The embedding is carried out by using scene detection. The LL4 sub-band coefficients of frames constitute the dataset to train the ELM in millisecond time. The output of the ELM is used to embed a binary watermark in th

FLAT

Zentrale Ergebnisse und Ausblick, of celestial bodies but with the environmental influences such as atmospheric pressure, wind, rainfall and ice. The harmonic analysis method is used to represent the influences of celestial bodies, while the SDW-ELM is used to represent the influences of meteorological factors and other unmodeled f

Visual-Acuity

Jan-Hendrik Passoth,Werner Rammertsolid (SS) and total organic carbon (TOC) selected from the correlation analysis of the 23 monthly water variables were included, with 8 years (2001–2008) data for training and the most recent 3 years (2009–2011) for testing. The modeling results showed that the prediction and forecast (based on dat

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周兴旺

法官