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   Articles with "incremental learning" as a keyword



Oxygen Content Control in the Electroslag Remelting Process: An Incremental Learning Strategy Based on Optimized Wasserstein Generative Adversarial Network with Gradient Penalty Data Augmentation

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recommendations! Published in 2024 at "steel research international"

DOI: 10.1002/srin.202400598

Abstract: Electroslag remelting (ESR) is essential for producing high‐end special steel, but its complex process and numerous influencing factors make quality control challenging. This study addresses oxygen content control during ESR using a big data machine… read more here.

Keywords: control; learning strategy; network; oxygen content ... See more keywords

Incremental learning with a homeostatic self-organizing neural model

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recommendations! Published in 2019 at "Neural Computing and Applications"

DOI: 10.1007/s00521-019-04112-0

Abstract: AbstractWe present a new self-organized neural model that we term resilient self-organizing tissue (ReST), which can be run as a convolutional neural network, possesses a $$c^\infty $$c∞ energy function as well as a probabilistic interpretation… read more here.

Keywords: neural model; incremental learning; self; learning homeostatic ... See more keywords
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Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories

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recommendations! Published in 2019 at "Journal of Signal Processing Systems"

DOI: 10.1007/s11265-019-01450-z

Abstract: For the past few years, Deep Neural Networks (DNNs) have achieved state-of-art performance in numerous challenging domains. To reach this performance, DNNs consist in large sets of parameters and complex architectures, which are trained offline… read more here.

Keywords: incremental learning; neural networks; binary associative; associative memories ... See more keywords

Federated Class-Incremental Learning with New-Class Augmented Self-Distillation

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recommendations! Published in 2024 at "Journal of Computer Science and Technology"

DOI: 10.1007/s11390-025-5186-5

Abstract: Federated learning (FL) enables collaborative model training among participants while guaranteeing the privacy of raw data. Mainstream FL methodologies overlook the dynamic nature of real-world data, particularly its tendency to grow in volume and diversify… read more here.

Keywords: class incremental; class; self distillation; new class ... See more keywords

Nonconvulsive epileptic seizure monitoring with incremental learning

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recommendations! Published in 2019 at "Computers in biology and medicine"

DOI: 10.1016/j.compbiomed.2019.103434

Abstract: Nonconvulsive epileptic seizures (NCSz) and nonconvulsive status epilepticus (NCSE) are two neurological entities associated with increment in morbidity and mortality in critically ill patients. In a previous work, we introduced a method which accurately detected… read more here.

Keywords: ncsz detection; incremental learning; nonconvulsive epileptic; method ... See more keywords

The role of prior knowledge in incremental associative learning: An empirical and computational approach

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recommendations! Published in 2019 at "Journal of Memory and Language"

DOI: 10.1016/j.jml.2019.03.006

Abstract: Abstract Our experiences are encoded in relation to existing knowledge, and learning of new information is influenced by what has already been learned. Although learning is often an incremental process spanning multiple repetitions, the influences… read more here.

Keywords: role prior; prior knowledge; incremental learning; knowledge incremental ... See more keywords
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Adaptive classification using incremental learning for seismic-volcanic signals with concept drift

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recommendations! Published in 2021 at "Journal of Volcanology and Geothermal Research"

DOI: 10.1016/j.jvolgeores.2021.107211

Abstract: Abstract The accurate labeling of the volcanic earthquake signals is a crucial task in order to estimate the increase in volcanic activity (among other parameters), which contributes to determine a state of volcanic unrest (as… read more here.

Keywords: classification using; order; strategy; adaptive classification ... See more keywords
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BNGBS: An efficient network boosting system with triple incremental learning capabilities for more nodes, samples, and classes

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recommendations! Published in 2020 at "Neurocomputing"

DOI: 10.1016/j.neucom.2020.06.100

Abstract: Abstract As an ensemble algorithm, network boosting enjoys a powerful classification ability but suffers from the tedious and time-consuming training process. To tackle the problem, in this paper, a broad network gradient boosting system (BNGBS)… read more here.

Keywords: incremental learning; network; system; boosting system ... See more keywords

The dual origin of lexical perseverations in aphasia: Residual activation and incremental learning

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recommendations! Published in 2020 at "Neuropsychologia"

DOI: 10.1016/j.neuropsychologia.2020.107603

Abstract: Lexical perseveration, the inappropriate repetition of a previous response, is common in aphasia. Two underlying mechanisms have been proposed: residual activation and incremental learning. Previous attempts to differentiate the two have relied on experimental paradigms… read more here.

Keywords: incremental learning; activation incremental; semantically related; residual activation ... See more keywords

A Multi-Tier Stacked Ensemble Algorithm to Reduce the Regret of Incremental Learning for Streaming Data

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recommendations! Published in 2018 at "IEEE Access"

DOI: 10.1109/access.2018.2868114

Abstract: Incremental Learning (IL) is an exciting paradigm that deals with classification problems based on a streaming or sequential data. IL aims to achieve the same level of prediction accuracy on streaming data as that of… read more here.

Keywords: incremental learning; streaming data; algorithm; multi tier ... See more keywords

Learning Automata Based Incremental Learning Method for Deep Neural Networks

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2907645

Abstract: Deep learning methods have got fantastic performance on lots of large-scale datasets for machine learning tasks, such as visual recognition and neural language processing. Most of the progress on deep learning in recent years lied… read more here.

Keywords: deep neural; training; neural networks; method ... See more keywords