This paper presents a color images region growing method based on online learning algorithm, which is used for content-based image retrieval systems.

论文阐述了一种基于在线学习算法的彩色图像区域增长法，用于解决基于内容的图像检索系统。

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By using CMAC neural network based on credit assignment this algorithm is implemented, and conventional CMAC's online learning speed and its accuracy are improved at the same time.

采用基于信任分配的CMAC神经网络实现了该算法，显著提高了传统CMAC在线学习的速度与准确性。

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To reduce the computational cost of extreme learning machine (ELM) online training, a new algorithm called local extreme learning machine (LELM) was proposed.

针对训练样本贯序输入时的极端学习机（ELM）训练问题，提出一种可实现在线训练的局域极端学习机（LELM）。

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To reduce the computational cost of extreme learning machine (ELM) online training, a new algorithm called local extreme learning machine (LELM) was proposed.

针对训练样本贯序输入时的极端学习机（ELM）训练问题，提出一种可实现在线训练的局域极端学习机（LELM）。

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