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- W2133238210 abstract "The present study discusses about the new textural feature extraction, its improvement and a comprehensive analysis of our previous Machine Learning based Spatio-Temporal (STML-HAB) Data Mining approach for HAB detection mentioned in Ref. [2]. This study is an elaborative analysis extending our first results presented in Ref. [2]. The additional Wavelet and GLCM textural features helped in improving the performance up to an accuracy of 0.9259 'K' using SeaWiFS sensor data. This is a significant improvement of almost 17% compared to our first results with an accuracy of (0.7513 'K')." @default.
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- W2133238210 date "2011-07-01" @default.
- W2133238210 modified "2023-09-25" @default.
- W2133238210 title "Comprehensive performance analysis of Spatio-Temporal Data Mining approach on multi-temporal coastal remote sensing datasets" @default.
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- W2133238210 doi "https://doi.org/10.1109/igarss.2011.6049592" @default.
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