Semantic-Gap-Oriented Feature Selection and Classifier Construction in Multilabel Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2020.2977133
Abstract: Multilabel learning focuses on assigning instances with different labels. In essence, the multilabel learning aims at learning a predictive function from feature space to a label space. The predictive function learning procedure can be regarded… read more here.
Keywords: feature selection; feature; semantic gap; multilabel learning ... See more keywords
Bridging the Semantic Gap Between Customer Needs and Design Specifications Using User-Generated Content
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DOI: 10.1109/tem.2020.3021698
Abstract: Although product design has been considered as a collaborative activity, progress in developing methods to facilitate the design process has been hampered by difficulties in building common bases among various stakeholders. Customers may only have… read more here.
Keywords: semantic gap; customer needs; design; product ... See more keywords
Shrinking the Semantic Gap: Spatial Pooling of Local Moment Invariants for Copy-Move Forgery Detection
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DOI: 10.1109/tifs.2023.3234861
Abstract: Copy-move forgery is a manipulation of copying and pasting specific patches from and to an image, with potentially illegal or unethical uses. Recent advances in the forensic methods for copy-move forgery have shown increasing success… read more here.
Keywords: semantic gap; move forgery; detection; copy move ... See more keywords