{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T16:03:14Z","timestamp":1743091394350,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319464534"},{"type":"electronic","value":"9783319464541"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-46454-1_23","type":"book-chapter","created":{"date-parts":[[2016,9,15]],"date-time":"2016-09-15T09:15:09Z","timestamp":1473930909000},"page":"366-381","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Network Flow Formulations for Learning Binary Hashing"],"prefix":"10.1007","author":[{"given":"Lopamudra","family":"Mukherjee","sequence":"first","affiliation":[]},{"given":"Jiming","family":"Peng","sequence":"additional","affiliation":[]},{"given":"Trevor","family":"Sigmund","sequence":"additional","affiliation":[]},{"given":"Vikas","family":"Singh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,9,16]]},"reference":[{"key":"23_CR1","doi-asserted-by":"crossref","unstructured":"Mukherjee, L., Singh, V., Peng, J.: Scale invariant cosegmentation for image groups. In: CVPR (2011)","DOI":"10.1109\/CVPR.2011.5995420"},{"key":"23_CR2","doi-asserted-by":"crossref","unstructured":"Mukherjee, L., Singh, V., Dyer, C.R.: Half-integrality based algorithms for cosegmentation of images. In: CVPR (2009)","DOI":"10.1109\/CVPR.2009.5206652"},{"key":"23_CR3","unstructured":"Weiss, Y., Torralba, A., Fergus, R.: Spectral hashing. In: NIPS (2008)"},{"key":"23_CR4","unstructured":"Kulis, B., Darrell, T.: Learning to hash with binary reconstructive embeddings. In: NIPS (2009)"},{"key":"23_CR5","doi-asserted-by":"crossref","unstructured":"Gong, Y., Lazebnik, S.: Iterative quantization: a procrustean approach to learning binary codes. In: CVPR (2011)","DOI":"10.1109\/CVPR.2011.5995432"},{"key":"23_CR6","unstructured":"Norouzi, M., Fleet, D.M.: Minimal loss hashing for compact binary codes. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11) (2011)"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, STOC 1998, pp. 604\u2013613. ACM, New York (1998)","DOI":"10.1145\/276698.276876"},{"key":"23_CR8","unstructured":"Liu, W., Mu, C., Kumar, S., Chang, S.: Discrete graph hashing. In: NIPS (2014)"},{"issue":"7","key":"23_CR9","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1016\/j.ijar.2008.11.006","volume":"50","author":"R Salakhutdinov","year":"2009","unstructured":"Salakhutdinov, R., Hinton, G.: Semantic hashing. Int. J. Approximate Reasoning 50(7), 969\u2013978 (2009)","journal-title":"Int. J. Approximate Reasoning"},{"key":"23_CR10","unstructured":"Krizhevsky, A., Hinton, G.E.: Using very deep autoencoders for content-based image retrieval. In: ESANN (2011)"},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Kulis, B., Grauman, K.: Kernelized locality-sensitive hashing for scalable image search. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 2130\u20132137. IEEE (2009)","DOI":"10.1109\/ICCV.2009.5459466"},{"key":"23_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1007\/978-3-642-33715-4_25","volume-title":"Computer Vision \u2013 ECCV 2012","author":"Y Weiss","year":"2012","unstructured":"Weiss, Y., Fergus, R., Torralba, A.: Multidimensional spectral hashing. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7576, pp. 340\u2013353. Springer, Heidelberg (2012). doi:\n                      10.1007\/978-3-642-33715-4_25"},{"key":"23_CR13","unstructured":"Liu, W., Wang, J., Kumar, S., Chang, S.: Hashing with graphs. In: ICML (2011)"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Mukherjee, L., Ravi, S.N., Ithapu, V.K., Holmes, T., Singh, V.: An NMF perspective on binary hashing. In: IEEE International Conference on Computer Vision (ICCV), pp. 4184\u20134192 (2015)","DOI":"10.1109\/ICCV.2015.476"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, D., Wang, J., Cai, D., Lu, J.: Self-taught hashing for fast similarity search. In: SIGIR, pp. 18\u201325 (2010)","DOI":"10.1145\/1835449.1835455"},{"key":"23_CR16","doi-asserted-by":"crossref","unstructured":"Lin, G., Shen, C., Suter, D., van den Hengel, A.: A general two-step approach to learning-based hashing. In: ICCV (2013)","DOI":"10.1109\/ICCV.2013.317"},{"key":"23_CR17","doi-asserted-by":"crossref","unstructured":"Shakhnarovich, G., Viola, P., Darrell, T.: Fast pose estimation with parameter-sensitive hashing. In: ICCV (2003)","DOI":"10.1109\/ICCV.2003.1238424"},{"key":"23_CR18","unstructured":"Neyshabur, B., Srebro, N., Salakhutdinov, R., Makarychev, Y., Yadollahpour, P.: The power of asymmetry in binary hashing. In: NIPS (2013)"},{"key":"23_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1007\/978-3-319-10584-0_17","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T Ge","year":"2014","unstructured":"Ge, T., He, K., Sun, J.: Graph cuts for supervised binary coding. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8695, pp. 250\u2013264. Springer, Heidelberg (2014). doi:\n                      10.1007\/978-3-319-10584-0_17"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Shen, F., Shen, C., Liu, W., Shen, H.T.: Supervised discrete hashing. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298598"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Li, H., Liu, W., Ji, H.: Two-stage hashing for fast document retrieval. In: ACL (2014)","DOI":"10.3115\/v1\/P14-2081"},{"issue":"4","key":"23_CR22","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1145\/263867.263872","volume":"44","author":"M Stoer","year":"1997","unstructured":"Stoer, M., Wagner, F.: A simple min-cut algorithm. J. ACM 44(4), 585\u2013591 (1997)","journal-title":"J. ACM"},{"issue":"11","key":"23_CR23","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.1109\/34.244673","volume":"15","author":"Z Wu","year":"1993","unstructured":"Wu, Z., Leahy, R.: An optimal graph theoretic approach to data clustering: theory and its application to image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1101\u20131113 (1993)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"23_CR24","doi-asserted-by":"publisher","first-page":"929","DOI":"10.1007\/s00224-006-1350-7","volume":"39","author":"K Andreev","year":"2006","unstructured":"Andreev, K., Racke, H.: Balanced graph partitioning. Theory Comput. Syst. 39(6), 929\u2013939 (2006)","journal-title":"Theory Comput. Syst."},{"key":"23_CR25","unstructured":"Chen, Y., Zhang, Y., Ji, X.: Size regularized cut for data clustering. In: Advances in Neural Information Processing Systems, pp. 211\u2013218 (2005)"},{"issue":"1\u20133","key":"23_CR26","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/S0166-218X(01)00341-9","volume":"123","author":"E Boros","year":"2002","unstructured":"Boros, E., Hammer, P.L.: Pseudo-Boolean optimization. Discrete Appl. Math. 123(1\u20133), 155\u2013225 (2002)","journal-title":"Discrete Appl. Math."},{"issue":"7","key":"23_CR27","doi-asserted-by":"publisher","first-page":"1274","DOI":"10.1109\/TPAMI.2007.1031","volume":"29","author":"V Kolmogorov","year":"2007","unstructured":"Kolmogorov, V., Rother, C.: Minimizing nonsubmodular functions with graph cuts-a review. IEEE Trans. Pattern Anal. Mach. Intell. 29(7), 1274\u20131279 (2007)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"23_CR28","unstructured":"Rother, C., Kohli, P., Feng, W., Jia, J.: Minimizing sparse higher order energy functions of discrete variables. In: IEEE Conference on Computer Vision and Pattern Recognition, 2009, CVPR 2009, pp. 1382\u20131389. IEEE (2009)"},{"key":"23_CR29","unstructured":"Rother, C., Kolmogorov, V., Lempitsky, V., Szummer, M.: Optimizing binary MRFs via extended roof duality. In: IEEE Conference on Computer Vision and Pattern Recognition, 2007, CVPR 2007, pp. 1\u20138. IEEE (2007)"},{"issue":"1","key":"23_CR30","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s10994-006-7550-1","volume":"65","author":"MF Balcan","year":"2006","unstructured":"Balcan, M.F., Blum, A., Vempala, S.: Kernels as features: on kernels, margins, and low-dimensional mappings. Mach. Learn. 65(1), 79\u201394 (2006)","journal-title":"Mach. Learn."},{"key":"23_CR31","doi-asserted-by":"crossref","unstructured":"Kahl, F., Strandmark, P.: Generalized roof duality for pseudo-boolean optimization. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 255\u2013262. IEEE (2011)","DOI":"10.1109\/ICCV.2011.6126250"},{"key":"23_CR32","unstructured":"Kolmogorov, V.: Generalized roof duality and bisubmodular functions. In: Advances in Neural Information Processing Systems, pp. 1144\u20131152 (2010)"},{"key":"23_CR33","unstructured":"Wang, J., Shen, H.T., Zhang, T.: A survey on learning to hash. MSRC Technical Report (2014)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2016"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-46454-1_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,10]],"date-time":"2020-10-10T01:42:39Z","timestamp":1602294159000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-46454-1_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319464534","9783319464541"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-46454-1_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"16 September 2016","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.eccv2016.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}