{"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","type":"journal_article","date_published":"2014-04-01T00:00:00Z","page":"824-830","arxiv":1,"status":"public","quality_controlled":"1","_id":"18414","issue":"4","intvolume":"        36","date_created":"2024-10-15T11:20:55Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.1207.1522"}],"citation":{"ieee":"J. Masci, M. M. Bronstein, A. M. Bronstein, and J. Schmidhuber, “Multimodal similarity-preserving hashing,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 36, no. 4. IEEE, pp. 824–830, 2014.","ama":"Masci J, Bronstein MM, Bronstein AM, Schmidhuber J. Multimodal similarity-preserving hashing. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. 2014;36(4):824-830. doi:<a href=\"https://doi.org/10.1109/tpami.2013.225\">10.1109/tpami.2013.225</a>","mla":"Masci, Jonathan, et al. “Multimodal Similarity-Preserving Hashing.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, vol. 36, no. 4, IEEE, 2014, pp. 824–30, doi:<a href=\"https://doi.org/10.1109/tpami.2013.225\">10.1109/tpami.2013.225</a>.","chicago":"Masci, Jonathan, Michael M. Bronstein, Alex M. Bronstein, and Jurgen Schmidhuber. “Multimodal Similarity-Preserving Hashing.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE, 2014. <a href=\"https://doi.org/10.1109/tpami.2013.225\">https://doi.org/10.1109/tpami.2013.225</a>.","apa":"Masci, J., Bronstein, M. M., Bronstein, A. M., &#38; Schmidhuber, J. (2014). Multimodal similarity-preserving hashing. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. IEEE. <a href=\"https://doi.org/10.1109/tpami.2013.225\">https://doi.org/10.1109/tpami.2013.225</a>","short":"J. Masci, M.M. Bronstein, A.M. Bronstein, J. Schmidhuber, IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (2014) 824–830.","ista":"Masci J, Bronstein MM, Bronstein AM, Schmidhuber J. 2014. Multimodal similarity-preserving hashing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(4), 824–830."},"pmid":1,"oa_version":"Preprint","publication_status":"published","volume":36,"publisher":"IEEE","publication_identifier":{"issn":["0162-8828"],"eissn":["1939-3539"]},"doi":"10.1109/tpami.2013.225","abstract":[{"text":"We introduce an efficient computational framework for hashing data belonging to multiple modalities into a single representation space where they become mutually comparable. The proposed approach is based on a novel coupled siamese neural network architecture and allows unified treatment of intra- and inter-modality similarity learning. Unlike existing cross-modality similarity learning approaches, our hashing functions are not limited to binarized linear projections and can assume arbitrarily complex forms. We show experimentally that our method significantly outperforms state-of-the-art hashing approaches on multimedia retrieval tasks.","lang":"eng"}],"scopus_import":"1","article_processing_charge":"No","author":[{"full_name":"Masci, Jonathan","first_name":"Jonathan","last_name":"Masci"},{"first_name":"Michael M.","full_name":"Bronstein, Michael M.","last_name":"Bronstein"},{"orcid":"0000-0001-9699-8730","full_name":"Bronstein, Alexander","first_name":"Alexander","last_name":"Bronstein","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"},{"last_name":"Schmidhuber","first_name":"Jurgen","full_name":"Schmidhuber, Jurgen"}],"oa":1,"extern":"1","external_id":{"arxiv":["1207.1522"],"pmid":["26353203"]},"language":[{"iso":"eng"}],"year":"2014","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","date_updated":"2024-12-12T13:04:27Z","month":"04","title":"Multimodal similarity-preserving hashing","day":"01"}