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

Publication Type:
Conference Proceeding
2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016, 2016
Issue Date:
Filename Description Size
07797084.pdfPublished version1.18 MB
Adobe PDF
Full metadata record
© 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.
Please use this identifier to cite or link to this item: