Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Inspired by the idea of co-training algorithm, in this paper  propose a novel remote sensing image segmentation approach using co-training strategy under variational Bayesian (VB) framework. Image data are characterized in two distinct views, i.e. two disjoint feature sets. A Gaussian mixture model (GMM) is employed for each view. On one hand, underlying structure of image content is inferred automatically with the factor analysis techniques. On the other hand, parameters are estimated in a bootstrap mode with the co-training strategy. In this manner, a satisfying performance can be achieved. Experimental analyses carried out on several different sets of high resolution optical images validate the proposed algorithm.
['Keming Chen', 'Zhenglong Li', 'Jian Cheng', 'Zhixin Zhou', 'Hanqing Lu']
I am writing a research paper on a idea A variational co-training framework for remote sensing image segmentation
[{"from": "human", "value": "I am writing a research paper on a idea A variational co-training framework for remote sensing image segmentation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Inspired by the idea of co-training algorithm, in this paper  propose a novel remote sensing image segmentation approach using co-training strategy under variational Bayesian (VB) framework. Image data are characterized in two distinct views, i.e. two disjoint feature sets. A Gaussian mixture model (GMM) is employed for each view. On one hand, underlying structure of image content is inferred automatically with the factor analysis techniques. On the other hand, parameters are estimated in a bootstrap mode with the co-training strategy. In this manner, a satisfying performance can be achieved. Experimental analyses carried out on several different sets of high resolution optical images validate the proposed algorithm."}]