A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
YFCC100M HybridNet fc6 Deep Features for Content-Based Image Retrieval
2016
Proceedings of the 2016 ACM Workshop on Multimedia COMMONS - MMCommons '16
This paper presents a corpus of deep features extracted from the YFCC100M images considering the fc6 hidden layer activation of the HybridNet deep convolutional neural network. For a set of random selected queries we made available k-NN results obtained sequentially scanning the entire set features comparing both using the Euclidean and Hamming Distance on a binarized version of the features. This set of results is ground truth for evaluating Content-Based Image Retrieval (CBIR) systems that
doi:10.1145/2983554.2983557
fatcat:ayqkkrvufbgmxoicy35iogneju