Results 41 to 50 of about 6,527,322 (289)
Class-Incremental Learning Based on Big Dataset Pre-Trained Models
IEEE Access, 2023 Deep neural networks have shown excellent performance in the field of pattern classification and are widely used. However, real-world data are often cannot be obtained at once, and the knowledge of old classes will be heavily forgotten when training new ...
Bin Wen, Qiuyu Zhu
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Incrementally Learned Angular Representations for Few-Shot Class-Incremental Learning
IEEE Access, 2023 The main challenge of FSCIL is the trade-off between underfitting to a new session task and preventing forgetting the knowledge for earlier sessions. In this paper, we reveal that the angular space occupied by the features within the embedded area is relatively narrow.
Inug Yoon, Jong-Hwan Kim 0001
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Class Incremental Learning With Large Domain Shift
IEEE AccessWe address an important and practical problem facing deep-learning-based image classification: class incremental learning with a large domain shift. Most previous efforts on class incremental learning focus on one aspect of the problem, i.e., learning to
Kamin Lee +4 more
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End-to-End Incremental Learning [PDF]
, 2018 Although deep learning approaches have stood out in recent years due to their state-of-the-art results, they continue to suffer from catastrophic forgetting, a dramatic decrease in overall performance when training with new classes added incrementally.
Francisco M. Castro +4 more
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IEEE Transactions on Neural Systems and Rehabilitation EngineeringThis paper presents a narrative review of incremental learning methods for myoelectric control, outlining both the historical trajectory and potential of adaptive prosthetic systems.
Evan Campbell +13 more
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Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning
Sensors, 2021 Recently, the interest in biometric authentication based on electrocardiograms (ECGs) has increased. Nevertheless, the ECG signal of a person may vary according to factors such as the emotional or physical state, thus hindering authentication. We propose
Junmo Kim +5 more
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International Journal of Networked and Distributed Computing (IJNDC), 2020 This article presents the threshold-based incremental learning model for a case-base updating approach that can support adaptive detection and incremental learning of Case-based Reasoning (CBR)-based automatic adaptable phishing detection.
San Kyaw Zaw, Sangsuree Vasupongayya
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Incremental multiclass open-set audio recognition
IJAIN (International Journal of Advances in Intelligent Informatics), 2022 Incremental learning aims to learn new classes if they emerge while maintaining the performance for previously known classes. It acquires useful information from incoming data to update the existing models.
Hitham Jleed, Martin Bouchard
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Dual population-based incremental learning for problem optimization in dynamic environments [PDF]
, 2003 Copyright @ 2003 Asia Pacific Symposium on Intelligent and Evolutionary SystemsIn recent years there is a growing interest in the research of evolutionary algorithms for dynamic optimization problems since real world problems are usually dynamic, which ...
Yang, S, Yao, X
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Incremental multi‐view correlated feature learning based on non‐negative matrix factorisation
IET Computer Vision, 2021 In real‐world applications, large amounts of data from multiple sources come in the form of streams. This makes multi‐view feature learning cost much time when new instances rise incrementally.
Liang Zhao +3 more
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