{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T09:42:48Z","timestamp":1759570968304,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032054609","type":"print"},{"value":"9783032054616","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-032-05461-6_22","type":"book-chapter","created":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T09:08:12Z","timestamp":1759568892000},"page":"335-346","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Aspect-Based Few-Shot Learning"],"prefix":"10.1007","author":[{"given":"Tim","family":"van Engeland","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vlado","family":"Menkovski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,5]]},"reference":[{"key":"22_CR1","unstructured":"Liberated pixel cup. http:\/\/lpc.opengameart.org\/. Accessed 01 Jan 2024"},{"key":"22_CR2","unstructured":"Universal LPC spritesheet character generator. https:\/\/github.com\/sanderfrenken\/Universal-LPC-Spritesheet-Character-Generator. Accessed 01 Jan 2024"},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"Che, Y., An, Y., Xue, H.: Boosting few-shot open-set recognition with multi-relation margin loss. In: IJCAI, pp. 3505\u20133513 (2023)","DOI":"10.24963\/ijcai.2023\/390"},{"key":"22_CR4","unstructured":"Finn, C., Abbeel, P., Levine, S.: Model-agnostic meta-learning for fast adaptation of deep networks. In: International Conference on Machine Learning, pp. 1126\u20131135. PMLR (2017)"},{"key":"22_CR5","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"22_CR6","doi-asserted-by":"crossref","unstructured":"Li, H., Eigen, D., Dodge, S., Zeiler, M., Wang, X.: Finding task-relevant features for few-shot learning by category traversal. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1\u201310 (2019)","DOI":"10.1109\/CVPR.2019.00009"},{"key":"22_CR7","unstructured":"Li, Y., Mandt, S.: Disentangled sequential autoencoder. In: International Conference on Machine Learning (2018)"},{"key":"22_CR8","unstructured":"Mettes, P., Pol, E., Snoek, C.: Hyperspherical prototype networks. Adv. Neural. Inf. Process. Syst. 32 (2019)"},{"key":"22_CR9","unstructured":"Nichol, A., Schulman, J.: Reptile: a scalable metalearning algorithm. arXiv preprint arXiv:1803.02999, vol. 2, no. 3, p. 4 (2018)"},{"key":"22_CR10","unstructured":"Parnami, A., Lee, M.: Learning from few examples: a summary of approaches to few-shot learning. arXiv preprint arXiv:2203.04291 (2022)"},{"key":"22_CR11","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: FaceNet: a unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"22_CR12","unstructured":"Snell, J., Swersky, K., Zemel, R.: Prototypical networks for few-shot learning. Adv. Neural. Inf. Process. Syst. 30 (2017)"},{"key":"22_CR13","unstructured":"Sohn, K.: Improved deep metric learning with multi-class n-pair loss objective. Adv. Neural. Inf. Process. Syst. 29 (2016)"},{"key":"22_CR14","doi-asserted-by":"crossref","unstructured":"Sung, F., Yang, Y., Zhang, L., Xiang, T., Torr, P.H., Hospedales, T.M.: Learning to compare: Relation network for few-shot learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1199\u20131208 (2018)","DOI":"10.1109\/CVPR.2018.00131"},{"key":"22_CR15","unstructured":"Vinyals, O., Blundell, C., Lillicrap, T., Wierstra, D., et\u00a0al.: Matching networks for one shot learning. Adv. Neural. Inf. Process. Syst. 29 (2016)"},{"issue":"7","key":"22_CR16","doi-asserted-by":"publisher","first-page":"926","DOI":"10.1109\/LSP.2018.2822810","volume":"25","author":"F Wang","year":"2018","unstructured":"Wang, F., Cheng, J., Liu, W., Liu, H.: Additive margin softmax for face verification. IEEE Signal Process. Lett. 25(7), 926\u2013930 (2018)","journal-title":"IEEE Signal Process. Lett."},{"key":"22_CR17","unstructured":"Yin, L., Menkovski, V., Liu, S., Pechenizkiy, M.: Hierarchical semantic segmentation using psychometric learning. arXiv preprint arXiv:2107.03212 (2021)"},{"key":"22_CR18","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-030-67661-2_10","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"L Yin","year":"2021","unstructured":"Yin, L., Menkovski, V., Pechenizkiy, M.: Knowledge elicitation using deep metric learning and psychometric testing. In: Hutter, F., Kersting, K., Lijffijt, J., Valera, I. (eds.) ECML PKDD 2020, Part II. LNCS (LNAI), vol. 12458, pp. 154\u2013169. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67661-2_10"},{"key":"22_CR19","doi-asserted-by":"crossref","unstructured":"Yin, L., Menkovski, V., Pei, Y., Pechenizkiy, M.: Semantic-based few-shot learning by interactive psychometric testing. arXiv preprint arXiv:2112.09201 (2021)","DOI":"10.1007\/978-3-031-01333-1_31"},{"key":"22_CR20","unstructured":"Zaheer, M., Kottur, S., Ravanbakhsh, S., Poczos, B., Salakhutdinov, R.R., Smola, A.J.: Deep sets. Adv. Neural. Inf. Process. Syst. 30 (2017)"},{"issue":"1","key":"22_CR21","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1109\/JPROC.2020.3004555","volume":"109","author":"F Zhuang","year":"2020","unstructured":"Zhuang, F., et al.: A comprehensive survey on transfer learning. Proc. IEEE 109(1), 43\u201376 (2020)","journal-title":"Proc. IEEE"}],"container-title":["Lecture Notes in Computer Science","Discovery Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-05461-6_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T09:08:21Z","timestamp":1759568901000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-05461-6_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783032054609","9783032054616"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-05461-6_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"5 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Discovery Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ljubljana","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Slovenia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dis2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ds2025.ijs.si\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}