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Reproducibility Companion Paper: Selective Deep Convolutional Features for Image Retrieval
Conference proceeding

Reproducibility Companion Paper: Selective Deep Convolutional Features for Image Retrieval

Tuan Hoang, Thanh-Toan Do, Ngai-Man Cheung, Michael Riegler, Jan Zahálka and ASSOC COMP MACHINERY
Proceedings of the 28th ACM International Conference on Multimedia, pp.4448-4452
ACM Conferences
MM '20: The 28th ACM International Conference on Multimedia
12/10/2020
DOI: https://doi.org/10.1145/3394171.3414814

Abstract

Computing methodologies -- Artificial intelligence -- Computer vision -- Computer vision representations -- Image representations
In this companion paper, firstly, we briefly summarize the contributions of our main manuscript: Selective Deep Convolutional Features for Image Retrieval, published in ACM MultiMedia 2017. In addition, we provide detail instructions together with pre-configured MATLAB scripts which allow experiments to be executed and to reproduce the results reported in our main manuscript effortlessly. The source code is available at https://github.com/hnanhtuan/selectiveConvFeatures_ACMMM_reproducibility.

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