Correction: A benchmark dataset for performance evaluation of multi-label remote sensing image Retrieval [Remote Sens., 10, (2018), (964)] DOI:10.3390/rs10060964

Abstract

In our paper [1], we presented a dense labeling dataset that can be used for not only single-label and multi-label remote sensing image retrieval but also pixel-based problems such as semantic segmentation. Prof. Begum Demir first constructed and defined a multi-label archive in [2]. During the labeling of our dataset, we improved and referred to Prof. Demir's multi-labels to construct our dense (pixel) labels. Therefore, our dataset can be viewed as an extension of Prof. Demir's multi-labels. After publication of the paper [1], it was found that we did not clearly clarify the different contributions between our work and Prof. Begum Demir's multi-labels in the published version of the paper. Hence, according to the Academic Editor's suggestions, we decided to make some changes to the title and the text to make our contributions much clearer.