Abstract: Due to the growth of digital images require efficient methods to annotate the images is sense. In this paper, a semi-supervised spectral clustering with relevance feedback is used to annotate digital photos which is overcome the local minima problem on clustering methods by using some labeled information given by users. Performance of the proposed method is tested on Corel 5K dataset and the results demonstrate the efficiency and accuracy of the proposed method compared with other clustering methods.
Sadeghzadeh, N., Shamsi, M., Rasouli Kenari, A. (2021). 'Image annotation using a semi-supervised spectral clustering algorithm', Soft Computing Journal, 3(1), pp. 20-35.
VANCOUVER
Sadeghzadeh, N., Shamsi, M., Rasouli Kenari, A. Image annotation using a semi-supervised spectral clustering algorithm. Soft Computing Journal, 2021; 3(1): 20-35.
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