{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T20:22:40Z","timestamp":1783542160102,"version":"3.55.0"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030306700","type":"print"},{"value":"9783030306717","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","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":[[2020]]},"DOI":"10.1007\/978-3-030-30671-7_2","type":"book-chapter","created":{"date-parts":[[2020,1,7]],"date-time":"2020-01-07T22:02:31Z","timestamp":1578434551000},"page":"17-31","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning"],"prefix":"10.1007","author":[{"given":"Issam H.","family":"Laradji","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reza","family":"Babanezhad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,1,9]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Bertinetto L, Valmadre J, Henriques JF, Vedaldi A, Torr PH (2016) Fully-convolutional Siamese networks for object tracking. In: ECCV","DOI":"10.1007\/978-3-319-48881-3_56"},{"key":"2_CR2","unstructured":"Bousmalis K, Trigeorgis G, Silberman N, Krishnan D, Erhan D (2016) Domain separation networks. In: NIPS"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Bousmalis K, Silberman N, Dohan D, Erhan D, Krishnan D (2017) Unsupervised pixel-level domain adaptation with generative adversarial networks. In: CVPR","DOI":"10.1109\/CVPR.2017.18"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Cao X, Wipf D, Wen F, Duan G, Sun J (2013) A practical transfer learning algorithm for face verification. In: ICCV","DOI":"10.1109\/ICCV.2013.398"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Deselaers T, Alexe B, Ferrari, V (2012) Weakly supervised localization and learning with generic knowledges. IJCV","DOI":"10.1007\/s11263-012-0538-3"},{"key":"2_CR6","unstructured":"Finn C, Abbeel P, Levine S (2017) Model-agnostic meta-learning for fast adaptation of deep networks"},{"key":"2_CR7","unstructured":"French G, Mackiewicz M, Fisher M (2018) Self-ensembling for visual domain adaptation. In: ICLR"},{"key":"2_CR8","unstructured":"Ganin Y, Lempitsky V (2014) Unsupervised domain adaptation by backpropagation"},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Ganin Y, Ustinova E, Ajakan H, Germain P, Larochelle H, Laviolette F, Marchand M, Lempitsky V (2016) Domain-adversarial training of neural networks. JMLR","DOI":"10.1007\/978-3-319-58347-1_10"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Ghifary M, Kleijn WB, Zhang M, Balduzzi D, Li W (2016) Deep reconstruction-classification networks for unsupervised domain adaptation. In: ECCV","DOI":"10.1007\/978-3-319-46493-0_36"},{"key":"2_CR11","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. In: NIPS"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Han EHS, Karypis, G, Kumar V (2001) Text categorization using weight adjusted k-nearest neighbor classification. In: PAKDD","DOI":"10.1007\/3-540-45357-1_9"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Hoffer E, Ailon N (2015) Deep metric learning using triplet network. International workshop on similarity-based pattern recognition","DOI":"10.1007\/978-3-319-24261-3_7"},{"key":"2_CR14","unstructured":"Hsu YC, Lv Z, Kira Z (2017) Learning to cluster in order to transfer across domains and tasks"},{"key":"2_CR15","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: NIPS"},{"key":"2_CR16","unstructured":"Laine S, Aila T (2016) Temporal ensembling for semi-supervised learning"},{"key":"2_CR17","doi-asserted-by":"crossref","unstructured":"Le Cun Y, Jackel L, Boser B, Denker J, Graf H, Guyon I, Henderson D, Howard R, Hubbard W (1989) Handwritten digit recognition: applications of neural network chips and automatic learning. IEEE Commun Mag","DOI":"10.1007\/978-3-642-76153-9_35"},{"key":"2_CR18","unstructured":"LeCun Y, The MNIST database of handwritten digits. http:\/\/yann.lecun.com\/exdb\/mnist\/"},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. IEEE","DOI":"10.1109\/5.726791"},{"key":"2_CR20","unstructured":"Li Y, Wang N, Shi J, Liu J, Hou X (2016) Revisiting batch normalization for practical domain adaptation"},{"key":"2_CR21","unstructured":"Liu MY, Tuzel O (2016) Coupled generative adversarial networks. In: NIPS"},{"key":"2_CR22","unstructured":"Long M, Cao Y, Wang J, Jordan MI (2015) Learning transferable features with deep adaptation networks"},{"key":"2_CR23","unstructured":"Peng X, Usman B, Kaushik N, Hoffman J, Wang D, Saenko K (2017) VisDA: the visual domain adaptation challenge"},{"key":"2_CR24","doi-asserted-by":"crossref","unstructured":"Pinheiro PO (2017) Unsupervised domain adaptation with similarity learning","DOI":"10.1109\/CVPR.2018.00835"},{"key":"2_CR25","doi-asserted-by":"crossref","unstructured":"Russo P, Carlucci FM, Tommasi T, Caputo B (2017) From source to target and back: symmetric bi-directional adaptive GAN","DOI":"10.1109\/CVPR.2018.00845"},{"key":"2_CR26","unstructured":"Saito K, Ushiku Y, Harada T (2017) Asymmetric tri-training for unsupervised domain adaptation"},{"key":"2_CR27","unstructured":"Sajjadi M, Javanmardi M, Tasdizen T (2016) Regularization with stochastic transformations and perturbations for deep semi-supervised learning. In: NIPS"},{"key":"2_CR28","unstructured":"Shi Z, Siva P, Xiang T (2017) Transfer learning by ranking for weakly supervised object annotation"},{"key":"2_CR29","doi-asserted-by":"crossref","unstructured":"Shrivastava A, Pfister T, Tuzel O, Susskind J, Wang W, Webb R (2017) Learning from simulated and unsupervised images through adversarial training. In: CVPR","DOI":"10.1109\/CVPR.2017.241"},{"key":"2_CR30","doi-asserted-by":"crossref","unstructured":"Song HO, Xiang Y, Jegelka S, Savarese S (2016) Deep metric learning via lifted structured feature embedding. In: CVPR","DOI":"10.1109\/CVPR.2016.434"},{"key":"2_CR31","doi-asserted-by":"crossref","unstructured":"Sun B, Saenko K (2016) Deep coral: correlation alignment for deep domain adaptation. In: ECCV","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"2_CR32","doi-asserted-by":"crossref","unstructured":"Sun B, Feng J, Saenko K (2016) Return of frustratingly easy domain adaptation. In: AAAI","DOI":"10.1609\/aaai.v30i1.10306"},{"key":"2_CR33","unstructured":"Tarvainen A, Valpola H (2017) Mean teachers are better role models: weight-averaged consistency targets improve semi-supervised deep learning results. In: NIPS"},{"key":"2_CR34","unstructured":"Tzeng E, Hoffman J, Zhang N, Saenko K, Darrell T (2014) Deep domain confusion: maximizing for domain invariance"},{"key":"2_CR35","doi-asserted-by":"crossref","unstructured":"Tzeng E, Hoffman J, Darrell T, Saenko K (2015) Simultaneous deep transfer across domains and tasks. In: ICCV","DOI":"10.1109\/ICCV.2015.463"},{"key":"2_CR36","doi-asserted-by":"crossref","unstructured":"Tzeng E, Hoffman J, Saenko K, Darrell T (2017) Adversarial discriminative domain adaptation","DOI":"10.1109\/CVPR.2017.316"},{"key":"2_CR37","doi-asserted-by":"crossref","unstructured":"Tzeng E, Hoffman J, Saenko K, Darrell T (2017) Adversarial discriminative domain adaptation. In: CVPR","DOI":"10.1109\/CVPR.2017.316"},{"key":"2_CR38","doi-asserted-by":"crossref","unstructured":"Wang M, Deng W (2018) Deep visual domain adaptation: a survey. Neurocomputing","DOI":"10.1016\/j.neucom.2018.05.083"},{"key":"2_CR39","unstructured":"Weinberger KQ, Saul LK (2009) Distance metric learning for large margin nearest neighbor classification. JMLR"},{"key":"2_CR40","unstructured":"Xing EP, Jordan MI, Russell SJ, Ng AY (2003) Distance metric learning with application to clustering with side-information. In: NIPS"}],"container-title":["Domain Adaptation for Visual Understanding"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-30671-7_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:17:39Z","timestamp":1665371859000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-30671-7_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030306700","9783030306717"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-30671-7_2","relation":{},"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"9 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}