{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:15:52Z","timestamp":1743059752464,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819785018"},{"type":"electronic","value":"9789819785025"}],"license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"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\/978-981-97-8502-5_21","type":"book-chapter","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T14:03:04Z","timestamp":1730383384000},"page":"289-303","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Knowledge Matching for Exemplar-Free Class-Incremental Learning"],"prefix":"10.1007","author":[{"given":"Runhang","family":"Chen","sequence":"first","affiliation":[]},{"given":"Xiao-Yuan","family":"Jing","sequence":"additional","affiliation":[]},{"given":"Haowen","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,1]]},"reference":[{"issue":"12","key":"21_CR1","doi-asserted-by":"publisher","first-page":"1028","DOI":"10.1016\/j.tics.2020.09.004","volume":"24","author":"R Hadsell","year":"2020","unstructured":"Hadsell, R., Rao, D., Rusu, A.A., Pascanu, R.: Embracing change: continual learning in deep neural networks. Trends Cogn. Sci. 24(12), 1028\u20131040 (2020)","journal-title":"Trends Cogn. Sci."},{"key":"21_CR2","doi-asserted-by":"publisher","first-page":"1180","DOI":"10.1109\/TIP.2020.3042086","volume":"30","author":"W Zhao","year":"2021","unstructured":"Zhao, W., Wu, X., Luo, J.: Cross-domain image captioning via cross-modal retrieval and model adaptation. IEEE Trans. Image Process. 30, 1180\u20131192 (2021)","journal-title":"IEEE Trans. Image Process."},{"issue":"6","key":"21_CR3","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.tics.2017.04.001","volume":"21","author":"ME Hasselmo","year":"2017","unstructured":"Hasselmo, M.E.: Avoiding catastrophic forgetting. Trends Cogn. Sci. 21(6), 407\u2013408 (2017)","journal-title":"Trends Cogn. Sci."},{"key":"21_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119731","volume":"651","author":"R Chen","year":"2023","unstructured":"Chen, R., Jing, X.Y., Wu, F., Zheng, W., Hao, Y.: Task-specific parameter decoupling for class incremental learning. Inf. Sci. 651, 119731 (2023)","journal-title":"Inf. Sci."},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Rebuffi, S., Kolesnikov, A., Sperl, G., Lampert, C.H.: iCaRL: incremental classifier and representation learning. In: CVPR, pp. 5533\u20135542 (2017)","DOI":"10.1109\/CVPR.2017.587"},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Douillard, A., Cord, M., Ollion, C., Robert, T., Valle, E.: PODNet: pooled outputs distillation for small-tasks incremental learning. In: ECCV, pp. 86\u2013102 (2020)","DOI":"10.1007\/978-3-030-58565-5_6"},{"key":"21_CR7","doi-asserted-by":"crossref","unstructured":"Zhao, B., Xiao, X., Gan, G., Zhang, B., Xia, S.: Maintaining discrimination and fairness in class incremental learning. In: CVPR, pp. 13205\u201313214 (2020)","DOI":"10.1109\/CVPR42600.2020.01322"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Wu, Y., Chen, Y., Wang, L., Ye, Y., Liu, Z., Guo, Y., et al.: Large scale incremental learning. In: CVPR, pp. 374\u2013382 (2019)","DOI":"10.1109\/CVPR.2019.00046"},{"key":"21_CR9","unstructured":"van\u00a0de Ven, G.M., Tolias, A.S.: Three scenarios for continual learning (2019). arXiv:1904.07734"},{"issue":"12","key":"21_CR10","doi-asserted-by":"publisher","first-page":"2935","DOI":"10.1109\/TPAMI.2017.2773081","volume":"40","author":"Z Li","year":"2018","unstructured":"Li, Z., Hoiem, D.: Learning without forgetting. IEEE Trans. Pattern Anal. Mach. Intell. 40(12), 2935\u20132947 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"21_CR11","unstructured":"Shin, H., Lee, J.K., Kim, J., Kim, J.: Continual learning with deep generative replay. In: NeurIPS, pp. 2990\u20132999 (2017)"},{"key":"21_CR12","unstructured":"Qi, D., Zhao, H., Li, S.: Better generative replay for continual federated learning. In: The Eleventh International Conference on Learning Representations (2023)"},{"key":"21_CR13","doi-asserted-by":"crossref","unstructured":"Szatkowski, F., Pyla, M., Przewi\u0229\u017alikowski, M., Cygert, S., Twardowski, B., Trzci\u0144ski, T.: Adapt your teacher: improving knowledge distillation for exemplar-free continual learning. In: WACV, pp. 1977\u20131987 (2024)","DOI":"10.1109\/WACV57701.2024.00198"},{"key":"21_CR14","unstructured":"Magistri, S., Trinci, T., Soutif, A., van\u00a0de Weijer, J., Bagdanov, A.D.: Elastic feature consolidation for cold start exemplar-free incremental learning. In: ICLR (2024)"},{"key":"21_CR15","doi-asserted-by":"crossref","unstructured":"Dhar, P., Singh, R.V., Peng, K., Wu, Z., Chellappa, R.: Learning without memorizing. In: CVPR, pp. 5138\u20135146 (2019)","DOI":"10.1109\/CVPR.2019.00528"},{"key":"21_CR16","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.neunet.2019.01.012","volume":"113","author":"GI Parisi","year":"2019","unstructured":"Parisi, G.I., Kemker, R., Part, J.L., Kanan, C., Wermter, S.: Continual lifelong learning with neural networks: a review. Neural Netw. 113, 54\u201371 (2019)","journal-title":"Neural Netw."},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Zhu, F., Zhang, X., Wang, C., Yin, F., Liu, C.: Prototype augmentation and self-supervision for incremental learning. In: CVPR, pp. 5871\u20135880 (2021)","DOI":"10.1109\/CVPR46437.2021.00581"},{"key":"21_CR18","doi-asserted-by":"crossref","unstructured":"Petit, G., Popescu, A., Schindler, H., Picard, D., Delezoide, B.: FeTrIL: feature translation for exemplar-free class-incremental learning. In: WACV, pp. 3900\u20133909 (2023)","DOI":"10.1109\/WACV56688.2023.00390"},{"key":"21_CR19","doi-asserted-by":"crossref","unstructured":"Liu, Y., Parisot, S., Slabaugh, G.G., Jia, X., Leonardis, A., Tuytelaars, T.: More classifiers, less forgetting: a generic multi-classifier paradigm for incremental learning. In: ECCV, pp. 699\u2013716 (2020)","DOI":"10.1007\/978-3-030-58574-7_42"},{"key":"21_CR20","doi-asserted-by":"publisher","first-page":"4069","DOI":"10.1038\/s41467-020-17866-2","volume":"11","author":"GM Van de Ven","year":"2020","unstructured":"Van de Ven, G.M., Siegelmann, H.T., Tolias, A.S.: Brain-inspired replay for continual learning with artificial neural networks. Nat. Commun. 11, 4069 (2020)","journal-title":"Nat. Commun."},{"key":"21_CR21","doi-asserted-by":"crossref","unstructured":"Zhai, J., Liu, X., Yu, L., Cheng, M.: Fine-grained knowledge selection and restoration for non-exemplar class incremental learning. In: Wooldridge, M.J., Dy, J.G., Natarajan, S. (eds.) AAAI, pp. 6971\u20136978 (2024)","DOI":"10.1609\/aaai.v38i7.28523"},{"key":"21_CR22","doi-asserted-by":"crossref","unstructured":"Zhu, K., Zhai, W., Cao, Y., Luo, J., Zha, Z.: Self-sustaining representation expansion for non-exemplar class-incremental learning. In: CVPR, pp. 9286\u20139295 (2022)","DOI":"10.1109\/CVPR52688.2022.00908"},{"issue":"8","key":"21_CR23","doi-asserted-by":"publisher","first-page":"6187","DOI":"10.1109\/JIOT.2020.3034621","volume":"8","author":"X Xu","year":"2021","unstructured":"Xu, X., Li, J., Yang, Y., Shen, F.: Toward effective intrusion detection using log-cosh conditional variational autoencoder. IEEE Internet Things Journal 8(8), 6187\u20136196 (2021)","journal-title":"IEEE Internet Things Journal"},{"key":"21_CR24","doi-asserted-by":"crossref","unstructured":"Simon, C., Koniusz, P., Harandi, M.: On learning the geodesic path for incremental learning. In: CVPR, pp. 1591\u20131600 (2021)","DOI":"10.1109\/CVPR46437.2021.00164"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-8502-5_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T14:20:09Z","timestamp":1730384409000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8502-5_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,1]]},"ISBN":["9789819785018","9789819785025"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8502-5_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,1]]},"assertion":[{"value":"1 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}