Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence

Deep Residual Learning for Image Recognition

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Adam: A Method for Stochastic Optimization

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Learning Multiple Layers of Features from Tiny Images

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On Information and Sufficiency

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Distilling the Knowledge in a Neural Network

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Overcoming catastrophic forgetting in neural networks

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Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1512.03385 · Cited by 4,196

iCaRL: Incremental Classifier and Representation Learning

Rebuffi, S.-A., Kolesnikov, A., Sperl, G., & Lampert, C. H. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.587 · Cited by 3,988

Natural Gradient Works Efficiently in Learning

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Theory of the backpropagation neural network

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Advancing Ultrasound Medical Continuous Learning with Task-Specific Generalization and Adaptability

Zhu, C., Lin, J., Tan, G., Zhu, N., Li, K., Wang, C., & Li, S. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10822568 · Cited by 6

A Class-Incremental Object Detection Method for Remote Sensing Images Based on Dynamic Multiprototype Matching

Hu, M.-T., Yin, W., Diao, W., Gao, X., & Sun, X. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3520831 · Cited by 3

Dynamic Expert Routing for Unsupervised Continual Anomaly Detection

Cai, Y., He, X., Tong, A., & Bai, X. (2025) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2025.3574429 · Cited by 3

Multi-Attribute Continual Learning for Blind Image Quality Assessment

Luo, Y., Liu, J., Zhou, W., & Jin, X. (2025) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas56072.2025.11043383 · Cited by 3

Similarity-based prototype reconstruction and feature reorganization for non-exemplar class incremental learning

Zhou, C., Sun, J., Palade, V., & Wu, X. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107837 · Cited by 3

Orthogonal Decoupled Continual Dictionary Learning for Multimode Process Monitoring

Huang, K., Zhang, Z., Wu, D., Yang, C., & Gui, W. (2025) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2025.3610198 · Cited by 3

Real-Time Enhancements of Digital Twins With Incremental Time Series Data in Networked Air-Ground Cooperative UAV Swarm Systems

Lee, M., Zhu, Y., Hu, Y., Pan, Y., Chen, J., Yao, Y., Yang, G., & Zhou, X. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3618724 · Cited by 3

Instance-Based Continual Learning: A Real-World Dataset and Baseline for Fresh Recognition

Xu, Z., Hu, H., Liu, L., Zhang, D., Zhang, S., & Tan, W. (2023) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3591209 · Cited by 3

TLCE: Transfer-Learning Based Classifier Ensembles for Few-Shot Class-Incremental Learning

Wang, S., Cao, Y. H., & Wu, T. (2024) · Neural Processing Letters · doi:10.1007/s11063-024-11605-0 · Cited by 3

Multi-Label Lifelong Machine Learning: A Scoping Review of Algorithms, Techniques, and Applications

Kassim, M. A., Viktor, H. L., & Michalowski, W. (2024) · IEEE Access · doi:10.1109/access.2024.3403569 · Cited by 4

Studying Forgetting in Faster R-CNN for Online Object Detection: Analysis Scenarios, Localization in the Architecture, and Mitigation

Wagner, B., Pellerin, D., & Huet, S. (2024) · IEEE Access · doi:10.1109/access.2024.3523637 · Cited by 3

Deep Generative Replay With Denoising Diffusion Probabilistic Models for Continual Learning in Audio Classification

Lee, H.-J., & Buu, S.-J. (2024) · IEEE Access · doi:10.1109/access.2024.3459954 · Cited by 4

Is Our Continual Learner Reliable? Investigating Its Decision Attribution Stability through SHAP Value Consistency

Cai, Y., Ling, S., Zhang, L., Pan, L., & Li, H. (2024) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00566 · Cited by 3

Transforming urban waste collection inventory: AI-Based container classification and Re-Identification

Galán, J., González, M., Moral, P., García‐Martín, Á., & Martínez, J. M. (2025) · Waste Management · doi:10.1016/j.wasman.2025.02.051 · Cited by 3

CLFace: A Scalable and Resource-Efficient Continual Learning Framework for Lifelong Face Recognition

Hasan, M. M., Sami, S. M., & Nasrabadi, N. M. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00497 · Cited by 4

A study on Few-shot Learning approach for Intrusion Detection System with Class Incremental Learning

Cao, Q. P. X., Tran, D. D., Ngo, S. T. T., Khoa, N. H., Duy, P. T., & Pham, V.-H. (2025) · International Conference on Intelligent Information Technology (ICIIT) · doi:10.1145/3731763.3731795 · Cited by 3

Balancing the Stability-Plasticity Dilemma with Online Stability Tuning for Continual Learning

Lee, A., Gomes, H. M., & Zhang, Y. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892055 · Cited by 3

NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning

Daram, A. R., & Kudithipudi, D. (2023) · Neuro Inspired Computational Elements Conference (NICE) · doi:10.1145/3584954.3584960 · Cited by 3

Online Continual Learning in Acoustic Scene Classification: An Empirical Study

Ha, D., Kim, M., & Jeong, C. Y. (2023) · Sensors · doi:10.3390/s23156893 · Cited by 3

Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy

Kim, J., Hong, S., Kim, C., Kim, J., Tiruneh, Y. Y., On, J., Song, J., Choi, S., & Baek, S. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446428 · Cited by 3

Doubly Perturbed Task Free Continual Learning

Lee, B. H., Oh, M.-H., & Chun, S. Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i12.29236 · Cited by 3

A memory-friendly class-incremental learning method for hand gesture recognition using HD-sEMG

Bai, Y., Wu, L., Duan, S., & Chen, X. (2024) · Medicine in Novel Technology and Devices · doi:10.1016/j.medntd.2024.100308 · Cited by 3

Simulated Data-Guided Incremental SAR ATR Through Feature Aggregation

Tang, Z., Sun, Y., Liu, C., Xu, Y., & Lei, L. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3418775 · Cited by 6

Two-dimensional hybrid incremental learning (2DHIL) framework for semantic segmentation of skin tissues

Imran, M., Akram, M. U., Tiwana, M. I., Salam, A. A., Hassan, T., & Greco, D. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.105147 · Cited by 3

Non-exemplar class-incremental learning for continual plant diagnosis

Li, D., Yin, Z., Zhao, Y., Zhao, Y., & Zhang, H. (2024) · Crop Protection · doi:10.1016/j.cropro.2024.107069 · Cited by 3

TactCLNet: Tactile Continual Learning Network Based on Generative Replay for Object Hardness Recognition

Liu, Y., Yi, Z., Fang, S., Zhang, Y., Wan, F., Yang, Z.-X., Lu, X., & Wu, X. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2024.3516378 · Cited by 3

Zero-shot incremental learning using spatial-frequency feature representations

Ren, J., Zhao, Y., Zhang, W., & Sun, C. (2025) · Scientific Reports · doi:10.1038/s41598-024-83649-0 · Cited by 3

Memory-efficient Continual Learning with Neural Collapse Contrastive

Dang, T.-A., Nguyen, V., Vu, N., & Vrain, C. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00772 · Cited by 3

Bias to Balance: New-Knowledge-Preferred Few-Shot Class-Incremental Learning via Transition Calibration

Zhang, H., Zhang, Z., Tan, X., Liu, J., Qu, Y., & Xie, Y. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3550429 · Cited by 3

A Two-Stage LoRA Strategy for Expanding Language Capabilities in Multilingual ASR Models

Kwok, C. Y., Liu, H., Yip, J. Q., Li, S., & Chng, E. S. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3578752 · Cited by 4

AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation

Sun, Z., Piao, S., Jin, H., Dong, C., Yue, L., Chen, W., & Zhou, L. (2025) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta68720.2025.11302476 · Cited by 3

Modular-Relatedness for Continual Learning

Shaker, A., Alesiani, F., & Yu, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-01333-1_23 · Cited by 3

Measuring Catastrophic Forgetting in Visual Question Answering

Greco, C., Plank, B., Fernández, R., & Raffaella Bernardi, B. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-9323-9_35 · Cited by 3

Incremental Learning in Synthetic Aperture Radar Images Using Openmax Algorithm

Oveis, A. H., Giusti, E., Ghio, S., Meucci, G., & Martorella, M. (2023) · IEEE Radar Conference (RadarConf) · doi:10.1109/radarconf2351548.2023.10149627 · Cited by 3

Streaming LifeLong Learning With Any-Time Inference

Banerjee, S., Verma, V. K., & Namboodiri, V. P. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10160358 · Cited by 3

Improving Prediction Backward-Compatiblility in NLP Model Upgrade with Gated Fusion

Lai, Y.-A., Mansimov, E., Xie, Y., & Zhang, Y. (2023) · Findings of the Association for Computational Linguistics: EACL · doi:10.18653/v1/2023.findings-eacl.74 · Cited by 6

Continual Learning for Out-of-Distribution Pedestrian Detection

Molahasani, M., Etemad, A., & Greenspan, M. (2023) · Proceedings - International Conference on Image Processing · doi:10.1109/icip49359.2023.10222758 · Cited by 3

Lifelong Scene Text Recognizer via Expert Modules

Xia, S., Geng, L., Liu, N., Sun, H., & Qin, J. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612062 · Cited by 3

The Batch Primary Components Transformer and Auto-Plasticity Learning Linear Units Architecture: Synthetic Image Generation Case

Selitskiy, S., Inoue, C., Schetinin, V., & Jakaite, L. (2023) · International Conference on Social Networks Analysis, Management and Security (SNAMS) · doi:10.1109/snams60348.2023.10375471 · Cited by 4

Continual Learning via Manifold Expansion Replay

Xu, Z., Tang, X., Shi, Y., Zhang, J., Yang, J. J., Chen, M., & Wei, X. (2023) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc53992.2023.10393967 · Cited by 3

Adaptive Shortcut Debiasing for Online Continual Learning

Kim, D., Park, D., Shin, Y., Bang, J., Song, H., & Lee, J.-G. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i12.29211 · Cited by 3

Contrastive Learning of Multivariate Gaussian Distributions of Incremental Classes for Continual Learning

Moon, H.-J., & Cho, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-61140-7_49 · Cited by 3

Attractive and repulsive training to address inter-task forgetting issues in continual learning

Choi, H., & Choi, D.-W. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.05.079 · Cited by 3

Learning to Transfer with von Neumann Conditional Divergence

Shaker, A., Yu, S., & Oñoro-Rubio, D. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i8.20797 · Cited by 3

TAG: Task-based Accumulated Gradients for Lifelong learningPreprint

Malviya, P., Ravindran, B., & Chandar, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.05155 · Cited by 5

How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of InterpolationPreprint

Lubana, E. S., Trivedi, P., Koutra, D., & Dick, R. P. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.02805 · Cited by 3

Incremental Learning in Multiple Limb Positions for Electromyography-Based Gesture Recognition using Hyperdimensional ComputingPreprint

Zhou, A., Muller, R., & Rabaey, J. M. (2021) · doi:10.36227/techrxiv.16643257 · Cited by 3

DiEvD-SF: Disruptive Event Detection Using Continual Machine Learning With Selective Forgetting

Seetha, A., Chouhan, S. S., Pilli, E. S., Raychoudhury, V., & Saha, S. (2024) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2024.3364544 · Cited by 2

Potential Knowledge Extraction Network for Class-Incremental Learning

Xi, X., Cao, G., Cao, W., Liu, Y., Li, Y., Wang, H., & Ren, H. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128923 · Cited by 2

Improving forward compatibility in class incremental learning by increasing representation rank and feature richness

Kim, J., Lee, W. C., Eo, M., & Rhee, W. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106969 · Cited by 2

TACLE: Task and Class-Aware Exemplar-Free Semi-Supervised Class Incremental Learning

Kalla, J., Kumar, R., & Biswas, S. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00675 · Cited by 2

Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation

Zhang, H. F., Yin, Z., Li, D., & Zhao, Y. (2025) · Agriculture · doi:10.3390/agriculture15091006 · Cited by 2

RACE: Robust adaptive and clustering elimination for noisy labels in continual learning

Xiaolong, Y., Lai, G., Meng, D., Cao, X., & Yang, X. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113783 · Cited by 2

Revisiting Clustering of Neural Bandits: Selective Reinitialization for Mitigating Loss of Plasticity

Su, Z., Dai, S.-H., & Zhang, X. (2025) · Knowledge Discovery and Data Mining · doi:10.1145/3711896.3737105 · Cited by 4

Slowly expanding neural network for class incremental learning

Xu, Z., Li, X., Chang, X., Zheng, W., & Wang, R. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.112213 · Cited by 2

Domain-continual learning for expanding the design space of deep generative modelling in nonlinear analysis of masonry

Adaileh, A., Ghiassi, B., & Briganti, R. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.106435 · Cited by 2

Rethinking Class-Incremental Learning From a Dynamic Imbalanced Learning Perspective

Wang, L., Xiang, L., Wang, Y., Wu, H., Yang, H., Liu, J., & He, Z. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3632688 · Cited by 3

Prompt-Driven Bit Extension Hashing for Continual Cross-Modal Retrieval

Liu, W., Wang, T., Li, F., Li, J., & Zhu, L. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3642760 · Cited by 2

Exemplar-Free Class Incremental Learning for Traffic Sign Classification

Liu, M., Ma, J., Kang, Q., Zhou, M., & Albeshri, A. A. (2025) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2025.3606740 · Cited by 3

Addressing catastrophic forgetting in class-incremental learning—a survey

Bako, J., & Kalita, J. K. (2026) · Artificial Intelligence Review · doi:10.1007/s10462-026-11575-w · Cited by 2

Intrinsic Preservation of Plasticity in Continual Quantum Learning

Chen, Y., & Zhang, S. (2026) · PRX Quantum · doi:10.1103/ry52-85ll · Cited by 4

Continual Semantic Segmentation With Tiny Memory

Yan, Q., Zhou, W., Liu, S., Dai, D., Wu, P., & Zhang, Y. (2026) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2026.3706775 · Cited by 2

Selecting Related Knowledge via Efficient Channel Attention for Online Continual Learning

Han, Y.-N., & Jian-we, L. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892898 · Cited by 2

Task-aware network: Mitigation of task-aware and task-free performance gap in online continual learning

Hong, Y., Park, S., & Byun, H. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126527 · Cited by 3

Generalizable Two-Branch Framework for Image Class-Incremental Learning

Wu, C., Chang, X., & Wang, R. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10447078 · Cited by 2

Autonomous Generative Feature Replay for Non-Exemplar Class-Incremental Learning

Zhang, Y., Shao, M., Shi, W., Xia, H., & Xia, S. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10448256 · Cited by 2

Incremental Learning with Maximum Dissimilarity Sampling Based Fault Diagnosis for Rolling Bearings

Fu, Y., He, J., Yang, L., & Luo, Z. (2024) · Communications in computer and information science · doi:10.1007/978-981-97-2275-4_17 · Cited by 2

Similarity-Based Adaptation for Task-Aware and Task-Free Continual Learning

Adel, T. (2024) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.15693 · Cited by 3

Double Confidence Calibration Focused Distillation for Task-Incremental Learning

Fu, Z., Wang, Z., Yu, C., Xu, X., & Li, D. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3418811 · Cited by 2

Adaptive Robust Continual Learning based on Bayesian Uncertainty Propagation

Kandel, D., & Dera, D. (2024) · International Conference on Information Fusion (FUSION) · doi:10.23919/fusion59988.2024.10706277 · Cited by 2

TS-ILM:Class Incremental Learning for Online Action Detection

Li, X., Cheng, J., Xia, Z., Chen, Z., Shi, J., Dong, Z., & Tashi, N. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681456 · Cited by 2

Decoding BatchNorm statistics via anchors pool for data-free models based on continual learning

Li, X., Wang, W., & Xu, G. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10904-w · Cited by 2

Towards Effective Authorship Attribution: Integrating Class-Incremental Learning

Rahgouy, M., Giglou, H. B., Tabassum, M., Feng, D., Das, A., Rahgooy, T., Dozier, G. V., & Seals, C. (2024) · IEEE International Conference on Cognitive Machine Intelligence (CogMI) · doi:10.1109/cogmi62246.2024.00018 · Cited by 3

KABI: Class-Incremental Learning via knowledge Amalgamation and Batch Identification

Li, C., Xu, W., Si, X., & Song, P. (2021) · International Conference on Innovation in Artificial Intelligence (ICIAI) · doi:10.1145/3461353.3461367 · Cited by 2

Metric Learning with Distillation for Overcoming Catastrophic Forgetting

Yu, P., He, J., Min, Q., & Zhu, Q. (2022) · Communications in computer and information science · doi:10.1007/978-981-19-1253-5_17 · Cited by 2

Learning and Transforming General Representations to Break Down Stability-Plasticity Dilemma

Murata, K., Ito, S., & Ohara, K. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26351-4_33 · Cited by 2

Overcoming Catastrophic Forgetting via Direction-Constrained Optimization

Teng, Y., Choromanska, A., Campbell, M. S., Lu, S., Ram, P., & Lior Horesh, C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26387-3_41 · Cited by 2

A Continual Learning Framework with Adaptive Synapses for Remaining Useful Life Prediction

Ren, X., Qiu, H., Chen, D., Peng, C., Qin, Y., & Wang, B. (2023) · Global Reliability and Prognostics and Health Management Conference (PHM) · doi:10.1109/phm-hangzhou58797.2023.10482788 · Cited by 2

L3Net: Localized and Layered Reparameterization for incremental learning

Luo, X., Zhang, H., Xie, Y., Zhang, H., Xu, X., & He, S. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107420 · Cited by 2

Continual Learning Techniques to Reduce Forgetting: A Comparative Study

Neeraj, & Nandal, P. (2025) · International Conference on Computational Intelligence, Communication Technology and Networking (CICTN) · doi:10.1109/cictn64563.2025.10932403 · Cited by 2

A Reality Check on Pre-training for Exemplar-free Class-Incremental Learning

Feillet, E., Popescu, A., & Hudelot, C. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00741 · Cited by 3

Enhancing Domain Adaptation in Continual Learning with Elastic Weight Consolidation: A Multi-Dataset Deep Learning Approach

Premalatha, R., Jayanthi, K. B., Rajasekaran, C., Sureshkumar, R., & Dhanalakshmi, R. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-87660-8_15 · Cited by 3

An Orthogonality-Based Dual-Memory Framework for Continual Text Classification

Zhang, H., Yu, L., Liang, B., Wang, H., Gui, L., & Xu, R. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3577396 · Cited by 2

Advances in incremental learning research

Hao, F., Qian, F., Jiahang, T., Zhao, H., Zhang, C., Xin, D., & Qian, H. (2025) · Journal of Image and Graphics · doi:10.11834/jig.240790 · Cited by 2

Frosting Weights for Better Continual Training

Zhu, X., Liu, F., Trajcevski, G., & Wang, D. (2019) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2019.00094 · Cited by 2

Class Incremental Learning With Task-Selection

Kim, E. S., Kim, J. U., Lee, S., Moon, S.-K., & Ro, Y. M. (2020) · Proceedings - International Conference on Image Processing · doi:10.1109/icip40778.2020.9190703 · Cited by 2

Retrospective Class Incremental Learning

Tao, Q., Loy, C. C., Cad, J., Get, Z., & See, S. C. W. (2021) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme51207.2021.9428257 · Cited by 2

Incremental Learning for Animal Pose Estimation using RBF k-DPP

Nayak, G. K., Shah, H., & Chakraborty, A. (2021) · British Machine Vision Conference (BMVC) · doi:10.5244/c.35.266 · Cited by 4

Diverse Memory for Experience Replay in Continual Learning

Krutsylo, A., & Morawiecki, P. (2022) · European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) · doi:10.14428/esann/2022.es2022-83 · Cited by 2

Prototype Representation Expansion in Incremental Learning

Mao, K., Luo, Y., Ren, Y., & Wang, R. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11317-x · Cited by 2

Create and Find Flatness: Building Flat Training Spaces in Advance for Continual Learning

Shi, W., Chen, Y., Zhao, Z., Lu, W., Yan, K., & Du, X. (2023) · Frontiers in artificial intelligence and applications · doi:10.3233/faia230509 · Cited by 3

A Model of Continual and Deep Learning for Aspect Based in Sentiment Analysis

Ramos, D. L., & Fuentes, F. J. A. (2023) · Journal of Automation Mobile Robotics & Intelligent Systems · doi:10.14313/jamris/1-2023/1 · Cited by 2

Flashback for Continual Learning

Mahmoodi, L., Harandi, M. T., & Moghadam, P. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00368 · Cited by 2

Mitigating Forgetting in Continual Learning via Contrasting Semantically Distinct Augmentations

Yu, S., & Chiu, W.-C. (2023) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc53992.2023.10393871 · Cited by 2

Probing Image Compression for Class-Incremental Learning

Yang, J., Duan, Z., Peng, A., Huang, Y., He, J., & Zhu, F. M. (2024) · Picture Coding Symposium · doi:10.1109/pcs60826.2024.10566365 · Cited by 3

Learning to Classify New Foods Incrementally Via Compressed Exemplars

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