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	Composite Object Relation Modeling for Few-Shot Scene Recognition 期刊论文 OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 5678-5691 作者: Song, Xinhang; Liu, Chenlong; Zeng, Haitao; Zhu, Yaohui; Chen, Gongwei \| 收藏 \| 浏览/下载：7/0 \| 提交时间：2023/12/04 Scene recognition few-shot learning graph modeling generalization ability
	Balancing prediction accuracy and generalization ability: A hybrid framework for modelling the annual dynamics of satellite-derived land surface temperatures 期刊论文 OAI收割 ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2019, 卷号: 151, 页码: 189-206 作者: Liu, Zihan; Zhan, Wenfeng; Lai, Jiameng; Hong, Falu; Quan, Jinling \| 收藏 \| 浏览/下载：75/0 \| 提交时间：2019/09/24 Land surface temperature Annual temperature cycle LST dynamics Prediction accuracy Generalization ability
	Balancing prediction accuracy and generalization ability: A hybrid framework for modelling the annual dynamics of satellite-derived land surface temperatures 期刊论文 OAI收割 ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2019, 卷号: 151, 页码: 189-206 作者: Liu, Zihan; Zhan, Wenfeng; Lai, Jiameng; Hong, Falu; Quan, Jinling \| 收藏 \| 浏览/下载：16/0 \| 提交时间：2019/09/24 Land surface temperature Annual temperature cycle LST dynamics Prediction accuracy Generalization ability
	Tracking error modeling of the theodolite based on GRNN method (EI CONFERENCE) 会议论文 OAI收割 2nd International Conference on Frontiers of Manufacturing and Design Science, ICFMD 2011, December 11, 2011 - December 13, 2011, Taichung, Taiwan 作者: Li M. 收藏 \| 浏览/下载：22/0 \| 提交时间：2013/03/25 To meet the requirement of high tracking accuracy as well as develop more reasonable evaluation method in this paper the General Regression Neural Network (GRNN) has been applied to build the tracking error model of the theodolite. First we analyze the nonlinear factors in the theodolite. Second we discuss the principle of GRNN including its structure the function as well as its priors. Third we build the tracking error model based on GRNN and verify the model through the different parameters. The result indicated that the network model based on GRNN has high accuracy and good generalization ability. It could instead the real system to a certain extent. The research in this paper has important value to the engineering practice.
	Multi-Task Rank Learning for Visual Saliency Estimation 期刊论文 OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2011, 卷号: 21, 期号: 5, 页码: 623-636 作者: Li, Jia; Tian, Yonghong; Huang, Tiejun; Gao, Wen \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2019/12/16 Generalization ability multi-task learning pair-wise rank learning visual saliency
	Study of the neural network constitutive models for turfy soil with different decomposition degree (EI CONFERENCE) 会议论文 OAI收割 2011 2nd International Conference on Mechanic Automation and Control Engineering, MACE 2011, July 15, 2011 - July 17, 2011, Inner Mongolia, China 作者: Nie L. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 The turfy soil is of a special humus soil. The decomposition degree is the main factor on the physical and mechanical properties of turfy soil. To build the turfy soil constitutive model there are a few shortages such as the calculation cumbersome and low accuracy for parameter value with the method of traditional models. Furthermore those methods did not reflect the influence of strength that effected by decomposition degree of the turfy soil. In this paper the relationship of stress-strain with different decomposition degrees of turfy soil was carried out through indoor tests. Based on above experimental results an improved method which divided into different zones according to different decomposition degrees of turfy soil and calculated combining with neural network constitutive model is put forward. The result shows that the neural network of turfy soil has good fitting precision and good generalization ability. It can fully describe the influence of the turfy soil. 2011 IEEE.
	A new early stopping algorithm for improving neural network generalization (EI CONFERENCE) 会议论文 OAI收割 2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009, October 10, 2009 - October 11, 2009, Changsha, Hunan, China 作者: Liu J.-G.; Wu X.-X. 收藏 \| 浏览/下载：22/0 \| 提交时间：2013/03/25 As generalization ability of neural network was restricted by overfitting problem in the network's training. Early stopping algorithm based on fuzzy clustering was put forward to solve this problem in this paper. Subtractive clustering and Fuzzy C-Means clustering (FCM) were combined to realize optimal division of training set validation set and test set. How to realize this algorithm in backpropagation (BP) network by utilizing neural network toolbox and fuzzy logic toolbox in MATLAB was dwelled on. Early stopping algorithm based on fuzzy clustering and other early stopping algorithms were applied in function approximation and pattern recognition problems in validation experiments. Experiments results indicate that early stopping algorithm based on fuzzy clustering has higher precision in comparison to other early stopping algorithms. Outputs of training set validation set and test set are more accordant. 2009 IEEE.
	Minimal consistent subset for hyper surface classification method 期刊论文 iSwitch采集 International journal of pattern recognition and artificial intelligence, 2008, 卷号: 22, 期号: 1, 页码: 95-108 作者: He, Qing; Zhao, Xiu-Rong; Shi, Zhong-Zhi 收藏 \| 浏览/下载：30/0 \| 提交时间：2019/05/10 Hyper surface classification (hsc) Minimal consistent subset (mcs) Sampling Generalization ability
	Minimal consistent subset for Hyper Surface Classification method 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2008, 卷号: 22, 期号: 1, 页码: 95-108 作者: He, Qing; Zhao, Xiu-Rong; Shi, Zhong-Zhi \| 收藏 \| 浏览/下载：13/0 \| 提交时间：2019/12/16 Hyper Surface Classification (HSC) Minimal Consistent Subset (MCS) sampling generalization ability