中国科学院机构知识库网格系统: 检索

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	(In)Congruence in Perceived Mother-child Cohesion and Informants' Depressive Symptoms: A Dyadic Response Surface Analysis 期刊论文 OAI收割 JOURNAL OF YOUTH AND ADOLESCENCE, 2023, 页码: 15 作者: Fang, Yuan; Chen, Zhiyan; Han, Buxin \| 收藏 \| 浏览/下载：23/0 \| 提交时间：2024/01/22 Mother-child cohesion (In)Congruent perceptions Depressive symptoms Longitudinal course Dyadic response surface analysis
	Insecure attachment may not hamper relationships: a dyadic fit perspective 期刊论文 OAI收割 CURRENT PSYCHOLOGY, 2022, 页码: 15 作者: Wang, Kexin; Li, Fugui; Xu, Jie; Chen, Shuang; Zhou, Mingjie \| 收藏 \| 浏览/下载：46/0 \| 提交时间：2022/12/16 Attachment Matching effect Romantic partners Polynomial regression Dyadic data analysis
	Can extroversion congruence promote online interaction? Evidence from college first-year students 期刊论文 OAI收割 PSYCH JOURNAL, 2022, 页码: 9 作者: Wang, Kexin; Chen, Shuang; Zhang, Jianxin; Deng, Yang; Zhang, Zheng \| 收藏 \| 浏览/下载：47/0 \| 提交时间：2022/02/11 congruence cross-sex friendship dyadic analysis extroversion social networking sites
	A novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Hu S.; Zhu M.; Wu C.; Song H.-J. 收藏 \| 浏览/下载：18/0 \| 提交时间：2013/03/25 In many computer vision tasks in order to improve the accuracy and robustness to the noise wavelet analysis is preferred for the natural multi-resolution property. However the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour the Zernike moments are introduced and a novel Starting-Point-lndependent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient precise and robust.
	A new approach for the removal of mixed noise based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light and indeed we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm the tracing of WTMM is not just tedious procedure computationally algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.