{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T06:57:08Z","timestamp":1781161028780,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":30,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819200672","type":"print"},{"value":"9789819200689","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-92-0068-9_5","type":"book-chapter","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T06:06:59Z","timestamp":1781158019000},"page":"59-70","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["IOF-DP: Iterative Inner\u2013Outer Fusion with\u00a0Dual-Projection for\u00a0Exemplar-Free Class Incremental Learning"],"prefix":"10.1007","author":[{"given":"Thi Thanh-Nga","family":"Hoang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mai Thanh-Thu","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quang-Tri","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan-Hung","family":"Ho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thi Quynh-Trang","family":"Pham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,1]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","unstructured":"Rebuffi, S.-A., Kolesnikov, A., Sperl, G., Lampert, C.H.: iCaRL: incremental classifier and representation learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2001\u20132010 (2017)","DOI":"10.1109\/CVPR.2017.587"},{"key":"5_CR2","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: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 3911\u20133920 (2023)","DOI":"10.1109\/WACV56688.2023.00390"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Feillet, E., Popescu, A., Hudelot, C.: A reality check on pre-training for exemplar-free class-incremental learning. In: 2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 7625\u20137636 (2025)","DOI":"10.1109\/WACV61041.2025.00741"},{"key":"5_CR4","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/S0079-7421(08)60536-8","volume":"24","author":"M McCloskey","year":"1989","unstructured":"McCloskey, M., Cohen, N.J.: Catastrophic interference in connectionist networks: the sequential learning problem. Psychol. Learn. Motiv. 24, 109\u2013165 (1989)","journal-title":"Psychol. Learn. Motiv."},{"key":"5_CR5","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."},{"issue":"13","key":"5_CR6","doi-asserted-by":"publisher","first-page":"3521","DOI":"10.1073\/pnas.1611835114","volume":"114","author":"J Kirkpatrick","year":"2017","unstructured":"Kirkpatrick, J., Pascanu, R., Rabinowitz, N., et al.: Overcoming catastrophic forgetting in neural networks. Proc. Natl. Acad. Sci. 114(13), 3521\u20133526 (2017)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"5_CR7","unstructured":"Zenke, F., Poole, B., Ganguli, S.: Continual learning through synaptic intelligence. In: International Conference on Machine Learning (ICML), pp. 3987\u20133995 (2017)"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M., Tuytelaars, T.: Memory aware synapses: learning what (not) to forget. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 139\u2013154 (2018)","DOI":"10.1007\/978-3-030-01219-9_9"},{"issue":"12","key":"5_CR9","doi-asserted-by":"publisher","first-page":"2935","DOI":"10.1109\/TPAMI.2017.2773081","volume":"40","author":"Z Li","year":"2017","unstructured":"Li, Z., Hoiem, D.: Learning without forgetting. IEEE Trans. Pattern Anal. Mach. Intell. 40(12), 2935\u20132947 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"5_CR10","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: European Conference on Computer Vision (ECCV), pp. 86\u2013102 (2020)","DOI":"10.1007\/978-3-030-58565-5_6"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Yu, L., Twardowski, B., Liu, X., et al.: Semantic drift compensation for class-incremental learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6982\u20136991 (2020)","DOI":"10.1109\/CVPR42600.2020.00701"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Goswami, D., Liu, Y., Twardowski, B., Van De Weijer, J.: FeCAM: exploiting the heterogeneity of class distributions in exemplar-free continual learning. In: Advances in Neural Information Processing Systems (NeurIPS), vol. 36, pp. 6582\u20136595 (2023)","DOI":"10.52202\/075280-0288"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Hou, S., Pan, X., Loy, C.C., Wang, Z., Lin, D.: Learning a unified classifier incrementally via rebalancing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 831\u2013839 (2019)","DOI":"10.1109\/CVPR.2019.00092"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Wu, Y., Chen, Y., Wang, L., et al.: Large scale incremental learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 374\u2013382 (2019)","DOI":"10.1109\/CVPR.2019.00046"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Belouadah, E., Popescu, A.: Il2M: class incremental learning with dual memory. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 583\u2013592 (2019)","DOI":"10.1109\/ICCV.2019.00067"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Castro, F.M., Mar\u00edn-Jim\u00e9nez, M.J., Guil, N., Schmid, C., Alahari, K.: End-to-end incremental learning. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 233\u2013248 (2018)","DOI":"10.1007\/978-3-030-01258-8_15"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Marczak, D., Twardowski, B., Trzci\u0144ski, T., Cygert, S.: MagMax: leveraging model merging for seamless continual learning. In: European Conference on Computer Vision (ECCV), pp. 379\u2013395 (2024)","DOI":"10.1007\/978-3-031-73013-9_22"},{"key":"5_CR18","doi-asserted-by":"publisher","first-page":"34056","DOI":"10.52202\/079017-1072","volume":"37","author":"L Jiao","year":"2024","unstructured":"Jiao, L., Lai, Q., Li, Y., Xu, Q.: Vector quantization prompting for continual learning. Adv. Neural Inf. Process. Syst. (NeurIPS) 37, 34056\u201334076 (2024)","journal-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)"},{"key":"5_CR19","unstructured":"Lopez-Paz, D., Ranzato, M.: Gradient episodic memory for continual learning. Adv. Neural Inf. Process. Syst. (NeurIPS) 30 (2017)"},{"key":"5_CR20","unstructured":"Chaudhry, A., Rohrbach, M., Elhoseiny, M., et al.: Continual learning with tiny episodic memories. In: Workshop on Multi-Task and Lifelong Reinforcement Learning (2019)"},{"key":"5_CR21","unstructured":"He, R., Fang, D., Chen, Y., et al.: REAL: Representation enhanced analytic learning for exemplar-free class-incremental learning. arXiv preprint arXiv:2403.13522 (2024)"},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Goswami, D., Soutif-Cormerais, A., Liu, Y., et al.: Resurrecting old classes with new data for exemplar-free continual learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 28525\u201328534 (2024)","DOI":"10.1109\/CVPR52733.2024.02695"},{"key":"5_CR23","first-page":"63268","volume":"37","author":"G Rype\u015b\u0107","year":"2024","unstructured":"Rype\u015b\u0107, G., Cygert, S., Trzci\u0144ski, T., Twardowski, B.: Task-recency bias strikes back: adapting covariances in exemplar-free class incremental learning. Adv. Neural Inf. Process. Syst. (NeurIPS) 37, 63268\u201363289 (2024)","journal-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)"},{"key":"5_CR24","unstructured":"Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning (ICML), pp. 1597\u20131607 (2020)"},{"key":"5_CR25","first-page":"22243","volume":"33","author":"T Chen","year":"2020","unstructured":"Chen, T., Kornblith, S., Swersky, K., Norouzi, M., Hinton, G.E.: Big self-supervised models are strong semi-supervised learners. Adv. Neural Inf. Process. Syst. (NeurIPS) 33, 22243\u201322255 (2020)","journal-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)"},{"key":"5_CR26","unstructured":"He, R., Fang, D., Xu, Y., et al.: Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning. arXiv preprint arXiv:2503.05423 (2025)"},{"key":"5_CR27","doi-asserted-by":"crossref","unstructured":"Feng, Y., Wang, X., Lu, Z., et al.: Recurrent Knowledge Identification and Fusion for Language Model Continual Learning. arXiv preprint arXiv:2502.17510 (2025)","DOI":"10.18653\/v1\/2025.acl-long.1328"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Zhu, F., Zhang, X.-Y., Wang, C., Yin, F., Liu, C.-L.: Prototype augmentation and self-supervision for incremental learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5871\u20135880 (2021)","DOI":"10.1109\/CVPR46437.2021.00581"},{"key":"5_CR29","first-page":"11602","volume":"35","author":"H Zhuang","year":"2022","unstructured":"Zhuang, H., Weng, Z., Wei, H., et al.: ACIL: analytic class-incremental learning with absolute memorization and privacy protection. Adv. Neural Inf. Process. Syst. (NeurIPS) 35, 11602\u201311614 (2022)","journal-title":"Adv. Neural Inf. Process. Syst. (NeurIPS)"},{"issue":"15","key":"5_CR30","first-page":"17237","volume":"38","author":"H Zhuang","year":"2024","unstructured":"Zhuang, H., He, R., Tong, K., Zeng, Z., Chen, C., Lin, Z.: DS-AL: a dual-stream analytic learning for exemplar-free class-incremental learning. Proc. AAAI Conf. Arti. Intell. 38(15), 17237\u201317244 (2024)","journal-title":"Proc. AAAI Conf. Arti. Intell."}],"container-title":["Communications in Computer and Information Science","Recent Challenges in Intelligent information and Database Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-0068-9_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T06:07:07Z","timestamp":1781158027000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-0068-9_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819200672","9789819200689"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-0068-9_5","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"1 June 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACIIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Intelligent Information and Database Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kaohsiung","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taiwan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 April 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 April 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aciids2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aciids.pwr.edu.pl\/2026\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}