Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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’).
['Balakrishna Gokaraju', 'Surya S. Durbha', 'Roger L. King', 'Nicolas H. Younan']
I am writing a research paper on a idea Comprehensive performance analysis of Spatio-Temporal Data Mining approach on multi-temporal coastal remote sensing datasets
[{"from": "human", "value": "I am writing a research paper on a idea Comprehensive performance analysis of Spatio-Temporal Data Mining approach on multi-temporal coastal remote sensing datasets"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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 \u2018K\u2019 using SeaWiFS sensor data. This is a significant improvement of almost 17% compared to our first results with an accuracy of (0.7513 \u2018K\u2019)."}]