Deep class-incremental learning: A survey
Deep models, eg, CNNs and Vision Transformers, have achieved impressive achievements
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
in many vision tasks in the closed world. However, novel classes emerge from time to time in …
Open-world machine learning: A review and new outlooks
Machine learning has achieved remarkable success in many applications. However,
existing studies are largely based on the closed-world assumption, which assumes that the …
existing studies are largely based on the closed-world assumption, which assumes that the …
Isolation and impartial aggregation: A paradigm of incremental learning without interference
This paper focuses on the prevalent stage interference and stage performance imbalance of
incremental learning. To avoid obvious stage learning bottlenecks, we propose a new …
incremental learning. To avoid obvious stage learning bottlenecks, we propose a new …
类别增量学习研究进展和性能评价
朱飞， 张煦尧， 刘成林 - 自动化学报, 2023 - aas.net.cn
机器学习技术成功地应用于计算机视觉, 自然语言处理和语音识别等众多领域. 然而,
现有的大多数机器学习模型在部署后类别和参数是固定的, 只能泛化到训练集中出现的类别 …
现有的大多数机器学习模型在部署后类别和参数是固定的, 只能泛化到训练集中出现的类别 …
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 …
Semantic knowledge guided class-incremental learning
Driven by practical needs, research on Class-Incremental Learning (CIL) has received more
and more attentions in recent years. A technical challenge to be conquered by CIL methods …
and more attentions in recent years. A technical challenge to be conquered by CIL methods …
One-shot replay: Boosting incremental object detection via retrospecting one object
Modern object detectors are ill-equipped to incrementally learn new emerging object
classes over time due to the well-known phenomenon of catastrophic forgetting. Due to data …
classes over time due to the well-known phenomenon of catastrophic forgetting. Due to data …
Class-Incremental Learning Method With Fast Update and High Retainability Based on Broad Learning System
Machine learning aims to generate a predictive model from a training dataset of a fixed
number of known classes. However, many real-world applications (such as health …
number of known classes. However, many real-world applications (such as health …
Few-shot Class-incremental Audio Classification Using Dynamically Expanded Classifier with Self-attention Modified Prototypes
Most existing methods for audio classification assume that the vocabulary of audio classes
to be classified is fixed. When novel (unseen) audio classes appear, audio classification …
to be classified is fixed. When novel (unseen) audio classes appear, audio classification …
DYSON: Dynamic Feature Space Self-Organization for Online Task-Free Class Incremental Learning
In this paper we focus on a challenging Online Task-Free Class Incremental Learning
(OTFCIL) problem. Different from the existing methods that continuously learn the feature …
(OTFCIL) problem. Different from the existing methods that continuously learn the feature …