Publications

Found 170 results
Author Title Type [ Year(Asc)]
Filters: Author is Gerald Friedland  [Clear All Filters]
In Press
Ye, Z., Choi J., & Friedland G. (In Press).  Supervised Deep Hashing for Highly Efficient Cover Song Detection. Proceedings of the 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR).
2020
Zhao, T., Choi J., & Friedland G. (2020).  DIME: An Online Tool for the Visual Comparison of Cross-modal Retrieval Models. International Conference on Multimedia Modeling. 729-733.
2019
Choi, J., Larson M., Friedland G., & Hanjalic A. (2019).  From Intra-Modal to Inter-Modal Space: Multi-Task Learning of Shared Representations for Cross-Modal Retrieval. Proceedings of 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM). 1-10.
Larson, M., Choi J., Slokom M., Erkin Z., Friedland G., & de Vries A. P. (2019).  Privacy and audiovisual content: Protecting users as big multimedia data grows bigger. Big Data Analytics for Large-Scale Multimedia Search.
Tschantz, M. Carl, & Friedland G. (2019).  Privacy Concerns of Multimodal Sensor Systems. The Handbook of Multimodal-Multisensor Interfaces: Foundations, User Modeling, and Common Modality Combinations . 1,
Friedland, G. (2019).  Reproducibility and Experimental Design for Machine Learning on Audio and Multimedia Data. Proceedings of the 27th ACM International Conference on Multimedia. 2709-2710.
Ye, Z., Choi J., & Friedland G. (2019).  Supervised Deep Hashing for Highly Efficient Cover Song Detection. Proceedings of the 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR).
2018
Tschantz, M. Carl, Egelman S., Choi J., Weaver N., & Friedland G. (2018).  The Accuracy of the Demographic Inferences Shown on Google's Ad Settings. Proceedings of the 2018 Workshop on Privacy in the Electronic Society. 33-41.
Choi, J., Akkus I. Ekin, Egelman S., Friedland G., Sommer R., Tschantz M. Carl, et al. (2018).  Cybercasing 2.0: You Get What You Pay For.
Ma, D., Friedland G., & Krell M. Michael (2018).  OrigamiSet1.0: Two New Datasets for Origami Classification and Difficulty Estimation. Proceedings of the 7th International Meeting on Origami in Science, Mathematics and Education (7OSME).

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