Results 31 to 40 of about 451,604 (277)
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 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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Storage Capacity of the Tilinglike Learning Algorithm [PDF]
, 2000 The storage capacity of an incremental learning algorithm for the parity machine, the Tilinglike Learning Algorithm, is analytically determined in the limit of a large number of hidden perceptrons.
Buhot, Arnaud, Gordon, Mirta B.
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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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Chunk Incremental Canonical Correlation Analysis [PDF]
Jisuanji kexue yu tansuo, 2022 For the large-scale dynamic data stream, incremental learning is an effective and efficient technique and is widely used in machine learning. Incremental dimensionality reduction algorithms have been proposed by many scholars.
PAN Yu, CHEN Xiaohong, LI Shunming, LI Jiyong
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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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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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