Interactive Domain Adaption for the Classification of Remote Sensing Images Using Active Learning


  • Lingam UP Department of Computer Science and Engineering, RVS college of Engineering and Technology, Coimbatore, India


Active learning (AL), domain adaptation (DA), image classification, support vector machine (SVM)


Interactive Domain Adaptation (IDA) technique based on active learning for the classification of remote sensing images. Interactive domain adaptation method is used for adapting the supervised classifier trained on a given remote sensing source image to make it suitable for classifying a different but related target image. The two images can be acquired in different locations and at different times. This method iteratively selects the most informative samples of the target image to be labeled and included in the training set and the source image samples are re weighted or removed from the training set on the basis of their disagreement with the target image classification problem. The consistent information available from the source image can be effectively exploited for the classification of the target image and for guiding the selection of new samples to be labeled, whereas the inconsistent information is automatically detected and removed. This approach significantly reduces the number of new labeled samples to be collected from the target image. Experimental results on both a multi spectral very high resolution and a hyper spectral data set confirm the effectiveness of the interactive domain adaptation for the classification of remote sensing using active learning method.


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How to Cite

Lingam, U. (2024). Interactive Domain Adaption for the Classification of Remote Sensing Images Using Active Learning. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(02), 545–548. Retrieved from



Original Research Article

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