Results 11 to 20 of about 448,103 (274)
Class-Incremental Learning of Convolutional Neural Networks Based on Double Consolidation Mechanism
IEEE Access, 2020 Class-incremental learning is a model learning technique that can help classification models incrementally learn about new target classes and realize knowledge accumulation.
Leilei Jin, Hong Liang, Changsheng Yang
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Reduce the Difficulty of Incremental Learning With Self-Supervised Learning
IEEE Access, 2021 Incremental learning requires a learning model to learn new tasks without forgetting the learned tasks continuously. However, when a deep learning model learns new tasks, it will catastrophically forget tasks it has learned before.
Linting Guan, Yan Wu
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Analysis of Chinese Patents associated with Incremental Clustering Algorithms: A Review
Journal of Computing Research and Innovation, 2022 With the advent of Internet-of-Things (IoT) and overall Information-Technology world, an enormous amount of data is getting generated dynamically and in real-time mode, in almost all domains of research and application systems.
Archana Chaudhari +2 more
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Incremental Cost-Sensitive Support Vector Machine With Linear-Exponential Loss
IEEE Access, 2020 Incremental learning or online learning as a branch of machine learning has attracted more attention recently. For large-scale problems and dynamic data problem, incremental learning overwhelms batch learning, because of its efficient treatment for new ...
Yue Ma, Kun Zhao, Qi Wang, Yingjie Tian
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Hierarchical incremental class learning with reduced pattern training [PDF]
, 2006 Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but closer examination reveals areas for potential improvement.
Bao, C, Guan, SU, Sun, RT
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Incremental Learning in Online Scenario [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Modern deep learning approaches have achieved great success in many vision applications by training a model using all available task-specific data. However, there are two major obstacles making it challenging to implement for real life applications: (1) Learning new classes makes the trained model quickly forget old classes knowledge, which is referred
He, Jiangpeng +3 more
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An incremental approach to genetic algorithms based classification [PDF]
, 2005 Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental
Guan, SU, Zhu, F
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Classification-oriented Incremental Dictionary Learning Algorithm [PDF]
Jisuanji gongcheng, 2017 Aiming at the problem that the computation cost of the traditional classification-oriented dictionary learning algorithms is too expensive on big datasets,this paper proposes a novel classification-oriented incremental dictionary learning algorithm.In ...
ZHANG Zhiwu,JING Xiaoyuan,WU Fei
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Class decomposition for GA-based classifier agents – A Pitt approach [PDF]
, 2004 Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental
Guan, SU, Zhu, F
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Incremental Task Learning with Incremental Rank Updates
, 2022 Code will be available at https://github.com/CSIPlab/task-increment-rank-update ...
Rakib Hyder +5 more
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