Results 31 to 40 of about 448,103 (274)
Incremental Object Detection Inspired by Memory Mechanisms in Brain [PDF]
Jisuanji kexue, 2023 Incremental learning is key to bridging the enormous gap between artificial intelligence and human intelligence,mea-ning that agents can learn several tasks sequentially from a continuous stream of correlated data without forgetting,just as humans do ...
SHANG Di, LYU Yanfeng, QIAO Hong
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Models of incremental concept formation [PDF]
, 1988 Given a set of observations, humans acquire concepts that organize those observations and use them in classifying future experiences. This type of concept formation can occur in the absence of a tutor and it can take place despite irrelevant and ...
Fisher, Douglas +2 more
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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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Incremental learning with respect to new incoming input attributes [PDF]
, 2001 Neural networks are generally exposed to a dynamic environment where the training patterns or the input attributes (features) will likely be introduced into the current domain incrementally.
Guan, SU, Li, SC
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New Generation Federated Learning
Sensors, 2022 With the development of the Internet of things (IoT), federated learning (FL) has received increasing attention as a distributed machine learning (ML) framework that does not require data exchange. However, current FL frameworks follow an idealized setup
Boyuan Li, Shengbo Chen, Zihao Peng
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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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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.
In-Ug Yoon, Jong-Hwan Kim
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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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Transfer Incremental Learning Using Data Augmentation
Applied Sciences, 2018 Deep learning-based methods have reached state of the art performances, relying on a large quantity of available data and computational power. Such methods still remain highly inappropriate when facing a major open machine learning problem, which ...
Ghouthi Boukli Hacene +4 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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