Unsupervised selective rank fusion for image retrieval tasks

Volume: 377, Pages: 182 - 199
Published: Feb 1, 2020
Abstract
Several visual features have been developed for content-based image retrieval in the last decades, including global, local and deep learning-based approaches. However, despite the huge advances in features development and mid-level representations, a single visual descriptor is often insufficient to achieve effective retrieval results in several scenarios. Mainly due to the diverse aspects involved in human visual perception, the combination of...
Paper Details
Title
Unsupervised selective rank fusion for image retrieval tasks
Published Date
Feb 1, 2020
Volume
377
Pages
182 - 199
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