[HTML][HTML] A survey on few-shot class-incremental learning
Large deep learning models are impressive, but they struggle when real-time data is not
available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for …
available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for …
Uncertainty-aware distillation for semi-supervised few-shot class-incremental learning
Given a model well-trained with a large-scale base dataset, few-shot class-incremental
learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples …
learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples …
Uncertainty-guided semi-supervised few-shot class-incremental learning with knowledge distillation
Class-Incremental Learning (CIL) aims at incrementally learning novel classes without
forgetting old ones. This capability becomes more challenging when novel tasks contain one …
forgetting old ones. This capability becomes more challenging when novel tasks contain one …
Few-shot class incremental learning leveraging self-supervised features
Abstract Few-Shot Class Incremental Learning (FSCIL) is a recently introduced Class
Incremental Learning (CIL) setting that operates under more constrained assumptions: only …
Incremental Learning (CIL) setting that operates under more constrained assumptions: only …
Few-shot learning for structural health diagnosis of civil infrastructure
XU Yang, FAN Yunlei, BAO Yuequan, LI Hui - Advanced Engineering …, 2024 - Elsevier
The successful development of deep learning and computer vision techniques has recently
revolutionized structural health diagnosis (SHD) during life-cycle construction, inspection …
revolutionized structural health diagnosis (SHD) during life-cycle construction, inspection …
Few-shot class-incremental learning: A survey
Few-shot Class-Incremental Learning (FSCIL) presents a unique challenge in machine
learning, as it necessitates the continuous learning of new classes from sparse labeled …
learning, as it necessitates the continuous learning of new classes from sparse labeled …
Gradient guided multi-scale feature collaboration networks for few-shot class-incremental remote sensing scene classification
W Wang, L Zhang, S Fu, P Ren, G Ren… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Few-shot class-incremental learning has recently received significant research focus in
remote sensing scene classification (FSCIL-RSSC). The success of FSCIL-RSSC relies on …
remote sensing scene classification (FSCIL-RSSC). The success of FSCIL-RSSC relies on …
Semantic-visual guided transformer for few-shot class-incremental learning
W Qiu, S Fu, J Zhang, C Lei… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Few-shot class-incremental learning (FSCIL) has recently attracted extensive attention in
various areas. Existing FSCIL methods highly depend on the robustness of the feature …
various areas. Existing FSCIL methods highly depend on the robustness of the feature …
Variable few shot class incremental and open world learning
Prior work on few-shot class incremental learning has operated with an unnatural
assumption: the number of ways and number of shots are assumed to be known and fixed …
assumption: the number of ways and number of shots are assumed to be known and fixed …
Rethinking Few-shot Class-incremental Learning: Learning from Yourself
YM Tang, YX Peng, J Meng, WS Zheng - European Conference on …, 2025 - Springer
Few-shot class-incremental learning (FSCIL) aims to learn sequential classes with limited
samples in a few-shot fashion. Inherited from the classical class-incremental learning …
samples in a few-shot fashion. Inherited from the classical class-incremental learning …