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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Forward Compatible Few-Shot Class-Incremental Learning
Da-Wei Zhou, Fuyun Wang, Han-Jia Ye, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 9036-9046
Open Access | Times Cited: 151

Showing 26-50 of 151 citing articles:

Learnable Distribution Calibration for Few-Shot Class-Incremental Learning
Binghao Liu, Boyu Yang, Lingxi Xie, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Vol. 45, Iss. 10, pp. 12699-12706
Open Access | Times Cited: 10
Concept agent network for zero-base generalized few-shot learning
Xuan Wang, Zhong Ji, Xiyao Liu, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access
Prompt-based learning for few-shot class-incremental learning
Jingjie Yuan, Hang Chen, Songsong Tian, et al.
Alexandria Engineering Journal (2025) Vol. 120, pp. 287-295
Closed Access
DFS: Dual-branch forward-looking simulation network for incremental learning of ancient Chinese characters
Qiuyue Ruan, Shanxiong Chen, Hailing Xiong, et al.
(2025) Vol. 13, Iss. 1
Open Access
Image–Text (IT)-Prompt: Prompt-Based Learning Framework Empowered by the Cluster-Based Nearest Class Mean (C-NCM) for Rehearsal-Free Contrastive Language–Image Pretraining (CLIP)-Based Continual Learning
Jiao Li, Wenlong Fu, Xiaolu Chen
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 2966-2966
Open Access
BEFM: A balanced and efficient fine-tuning model in class-incremental learning
Lize Liu, Jian Ji, Lei Zhao
Knowledge-Based Systems (2025), pp. 113298-113298
Closed Access
ICARE: cross-domain text classification with incremental class-aware representation and distillation learning
Son Duong, Truong X. Tran, Hai Anh Tran
International Journal of Machine Learning and Cybernetics (2025)
Closed Access
HDCPAA: a few-shot class-incremental learning model for remote sensing image recognition
Peng Li, Cunqian Feng, Xiaowei Hu, et al.
Neurocomputing (2025), pp. 130043-130043
Open Access
FILP-3D: Enhancing 3D few-shot class-incremental learning with pre-trained vision-language models
Wan Xu, Tianyu Huang, Tianyuan Qu, et al.
Pattern Recognition (2025), pp. 111558-111558
Closed Access
Using samples with label noise for robust continual learning
Hongyi Nie, Shiqi Fan, Yang Liu, et al.
Neural Networks (2025) Vol. 188, pp. 107422-107422
Closed Access
A prompt regularization approach to enhance few-shot class-incremental learning with Two-Stage Classifier
Meilan Hao, Y. T. Gu, Kejian Dong, et al.
Neural Networks (2025), pp. 107453-107453
Closed Access
Integrating Synaptic Synergy Prompt and Optimized Prototype Classifiers to Enhance Few-Shot Class-Incremental Learning
Meilan Hao, Yong Cai, Xiaoqing Lv, et al.
(2025)
Closed Access
Uncertainty-guided recurrent prototype distillation for graph few-shot class-incremental learning
Ning Zhu, Shaofan Wang, Sun Yan-feng, et al.
Multimedia Systems (2025) Vol. 31, Iss. 3
Closed Access
Aggregatedf-average neural network applied to few-shot class incremental learning
Mathieu Vu, Émilie Chouzenoux, Ismail Ben Ayed, et al.
Signal Processing (2025), pp. 110054-110054
Closed Access
Few-Shot Class-Incremental SAR Target Recognition via Cosine Prototype Learning
Yan Zhao, Lingjun Zhao, Ding Ding, et al.
IEEE Transactions on Geoscience and Remote Sensing (2023) Vol. 61, pp. 1-18
Closed Access | Times Cited: 9
Mine-Distill-Prototypes for Complete Few-Shot Class-Incremental Learning in Image Classification
Yuan Tai, Yihua Tan, Shengzhou Xiong, et al.
IEEE Transactions on Geoscience and Remote Sensing (2023) Vol. 61, pp. 1-13
Closed Access | Times Cited: 8
Class similarity weighted knowledge distillation for few shot incremental learning
Feidu Akmel, Fanman Meng, Qingbo Wu, et al.
Neurocomputing (2024) Vol. 584, pp. 127587-127587
Closed Access | Times Cited: 3
Rethinking few-shot class-incremental learning: A lazy learning baseline
Zhili Qin, Wei Han, Jiaming Liu, et al.
Expert Systems with Applications (2024) Vol. 250, pp. 123848-123848
Closed Access | Times Cited: 3
CA-CLIP: category-aware adaptation of CLIP model for few-shot class-incremental learning
Yuqiao Xu, Shucheng Huang, Haoliang Zhou
Multimedia Systems (2024) Vol. 30, Iss. 3
Closed Access | Times Cited: 3
Revisiting Few-Shot Learning From a Causal Perspective
Guoliang Lin, Yongheng Xu, Hanjiang Lai, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 11, pp. 6908-6919
Open Access | Times Cited: 3
Class-incremental learning with Balanced Embedding Discrimination Maximization
Qinglai Wei, Weiqin Zhang
Neural Networks (2024) Vol. 179, pp. 106487-106487
Closed Access | Times Cited: 3
A cognition-driven framework for few-shot class-incremental learning
Xuan Wang, Zhong Ji, Yanwei Pang, et al.
Neurocomputing (2024) Vol. 600, pp. 128118-128118
Closed Access | Times Cited: 3
Pre-trained Vision and Language Transformers are Few-Shot Incremental Learners
Keon-Hee Park, Kyungwoo Song, Gyeong-Moon Park
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 23881-23890
Closed Access | Times Cited: 3
EEG-Based Motor Imagery Recognition Framework via Multisubject Dynamic Transfer and Iterative Self-Training
He Wang, Peiyin Chen, Meng Zhang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 8, pp. 10698-10712
Closed Access | Times Cited: 8
Inherit With Distillation and Evolve With Contrast: Exploring Class Incremental Semantic Segmentation Without Exemplar Memory
Danpei Zhao, Bo Yuan, Zhenwei Shi
IEEE Transactions on Pattern Analysis and Machine Intelligence (2023) Vol. 45, Iss. 10, pp. 11932-11947
Open Access | Times Cited: 8

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