Automatic Image Captions for Lightly Labelled Images IJTSRD


We initiate a new distance metric learning technique recognized as ambiguously supervised structural metric learning to find out discriminative Mahalanobis distance metric that is based on weak supervision data. For improving the performance, two affinity matrices are combined to get a fused affinity matrix which is used for face naming. When specified a collection of images, in which each of the image contains numerous faces and is linked by few names in corresponding caption, the purpose of face naming is to infer acceptable name for each face. Here we introduce two methods to correspondingly get hold of two discriminative affinity matrices by means of learning from the images of weakly labelled. For initial affinity matrix obtaining, we put forward a new method known as regularized low-rank representation by incorporation of weakly supervised information into low-rank representation with the intention that affinity matrix is obtained from resulting reconstruction coefficient matrix.

by Raju Janagam | K. Yakub Reddy”Automatic Image Captions for Lightly Labelled Images”

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018,

URL: http://www.ijtsrd.com/papers/ijtsrd10786.pdf

http://www.ijtsrd.com/engineering/computer-engineering/10786/automatic-image-captions-for-lightly-labelled-images/raju-janagam

call for paper Forestry Engineering, international journal Software Engineering, ugc approved journals for engineering




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