Results 11 to 20 of about 452,378 (262)
Deep Error-Correcting Output Codes
Algorithms, 2023 Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval.
Li-Na Wang +4 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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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
core +1 more source
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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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 Incremental Learning Method Integrating Balance Weight and Self-supervision [PDF]
Jisuanji kexue yu tansuoIn view of the catastrophic forgetting phenomenon of knowledge in class incremental learning in image classification, the existing class incremental learning methods focus on the correction of the unbalanced offset of the model classification layer ...
GONG Jiayi, XU Xinlei, XIAO Ting, WANG Zhe
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Survey of Federated Incremental Learning [PDF]
Jisuanji kexueFederated learning,with its unique distributed training mode and secure aggregation mechanism,has become a research hotspot in recent years.However,in real-life scenarios,local model training often faces new data,leading to catastrophic forgetting of old
XIE Jiachen, LIU Bo, LIN Weiwei , ZHENG Jianwen
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An Optimized Class Incremental Learning Network with Dynamic Backbone Based on Sonar Images
Journal of Marine Science and Engineering, 2023 Class incremental learning with sonar images introduces a new dimension to underwater target recognition. Directly applying networks designed for optical images to our constructed sonar image dataset (SonarImage20) results in significant catastrophic ...
Xinzhe Chen, Hong Liang
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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.
Alahari, Karteek +4 more
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Using Domain Adaptation for Incremental SVM Classification of Drift Data
Mathematics, 2022 A common assumption in machine learning is that training data is complete, and the data distribution is fixed. However, in many practical applications, this assumption does not hold.
Junya Tang, Kuo-Yi Lin, Li Li
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