SLNSW-UTS: A Historical Image Dataset for Image Multi-Labeling and Retrieval

Publication Type:
Conference Proceeding
Citation:
2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016, 2016
Issue Date:
2016-12-22
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© 2016 IEEE. This paper introduces a dataset of historical images created by the State Library of New South Wales and the University of Technology Sydney (UTS). The dataset has a total of 29713 images with 119 unique labels. Each image contains multiple labels. We use a CNN-based framework to explore the feasibility of our dataset in image multi-labeling and retrieval research, and extract semantic level image features for future research use. The experiment results illustrate that effective deep learning models can be trained on our dataset. We also introduce five applications that can be studied on our historical image dataset.
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