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	Applying maximally stable extremal regions and local binary patterns for guide-wire detecting in percutaneous coronary intervention 期刊论文 IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 13, 页码: 2579-2586 作者: Pusit, Prasong; Xie, Xiao-Liang; Hou, Zeng-Guang 收藏 \| 浏览/下载：12/0 \| 提交时间：2020/03/30 blood vessels medical image processing surgery image sequences video signal processing image filtering object detection X-ray imaging object tracking stroke width variation filter region detection local binary patterns guide-wire recognition conventional MSER methods maximally stable extremal regions guide-wire position anatomical skeleton contours training data X-ray video sequence percutaneous coronary intervention surgery region area range filter X-ray video monitoring guide-wire tip detection modified multifilters training templates
	Automatic ear detection and feature extraction using Geometric Morphometrics and convolutional neural networks 期刊论文 IET BIOMETRICS, 2017, 卷号: 6, 期号: 3 作者: Cintas, Celia; Quinto-Sanchez, Mirsha; Acuna, Victor; Paschetta, Carolina; de Azevedo, Soledad 收藏 \| 浏览/下载：24/0 \| 提交时间：2019/12/05 learning (artificial intelligence) neural nets feature extraction computational geometry image matching biometrics (access control) feature extraction geometric morphometrics phenotypic information anatomical structure identification fingerprints iris patterns facial traits ear structure ear biometric markers nonintrusive method facial expressions phenotypic attributes deep-learning algorithms automatic ear detection 2D landmarks convolutional neural network training morphometric landmarks human-assisted landmark matching feature vectors people identification
	A new face feature extraction method based on fusing lbp and dbns features 期刊论文 International Journal of Innovative Computing, Information and Control, 2016, 卷号: 12, 期号: 4, 页码: 1353-1364 作者: Wang, Yan; Wang, Yunyun 收藏 \| 浏览/下载：39/0 \| 提交时间：2020/11/14 Extraction Feature extraction Knowledge acquisition Machine learning Textures Deep belief networks Different resolutions Extreme learning machine Face feature extraction FERET face database Local binary patterns Local characteristics Network training
	A local texture-constrained super-resolution method 期刊论文 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, 卷号: 7674 LNCS, 页码: 285-293 作者: Liu, Q.; Wang, Y.; Zhang, Z. 收藏 \| 浏览/下载：5/0 \| 提交时间：2020/01/06 Embedding method High resolution High resolution image Image super-resolution LBP Local binary patterns Local Texture neighbor embedding SSIM Structural similarity Superresolution methods Texture similarity Training image Content based retrieval Data processing Optical resolving power Textures Image reconstruction
	Prediction of concrete strength using fuzzy neural networks 会议论文 Haikou, China, June 18, 2011 - June 20, 2011 作者: Xu, Jing; Wang, Xiuli 收藏 \| 浏览/下载：7/0 \| 提交时间：2020/11/15 Algebra Building materials Civil engineering Compressive strength Construction equipment Forecasting Fuzzy inference Fuzzy logic Fuzzy systems Learning algorithms Least squares approximations Mathematical models Network architecture Adaptive neuro-fuzzy inference system Automatic-learning Average relative error Compressive strength of concrete Concrete strength Concrete strength prediction Condition parameters Expert experience Fuzzy logic inference Fuzzy Neural Networks (FNN) Gradient Descent method Hybrid-learning algorithm Input and outputs Input-output data Intelligent prediction Least squares methods Parameter set Power functions Practical engineering Prediction model Rebound value Relative standard error Specific equations Strength values Takagi-sugeno Test results Training patterns
	汉语语音识别产品走向实用的途径会议论文第九届全国人机语音通讯学术会议论文集, Proceedings of the 9th National Conference on Man-Machine Speech Communication, 第九届全国人机语音通讯学术会议, 9th National Conference on Man-Machine Speech Communication, 中国安徽黄山, CNKI, 中文信息学会语音信息专业委员会、中国声学学会语言、听觉和音乐声学分会、中国语言学会语音学分会方棣棠; 李树青; Fang Ditang; Li Shuqing 收藏 \| 浏览/下载：3/0
	Non-stationary vibration signal analysis and fault diagnosis method of aircraft power plant using wavelet network 会议论文 Chinese Control and Decision Conference 2008, CCDC 2008, Yantai, Shandong, China, July 2, 2008 - July 4, 2008 作者: Zhao, Jianming; Liu, Jinjun 收藏 \| 浏览/下载：4/0 \| 提交时间：2017/01/17 Electric fault currents Aircraft Curve fitting Electric power plants Least squares approximations Power plants Signal analysis Signal processing Speech recognition Systems engineering Telecommunication Wavelet transforms Aero engines Aeroengine Eigenvectors Fault diagnosis Fault diagnosis method Fault patterns Feature vectors Multi-resolution analysis Network performances Network structures Non-stationary Pattern recognition Recursive orthogonal least squares algorithm Self-organizing learning Self-organizing learning array Simulation results Trained network Training and testing Vibration signal analysis Wavelet networks Wavelet transform
	Detection and tracking of low contrast targets based on integertype lifting wavelet transform (EI CONFERENCE) 会议论文 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Wang L.; Shen X.; Wang Y. 收藏 \| 浏览/下载：12/0 \| 提交时间：2013/03/25 This paper presents a method for detecting and tracking of low contrast targets. The new method uses an integer-type lifting wavelet transform and the proposed method doesn't extract patterns similar to a template but finds parts having the same feature in the targets. We utilize one of integer-type lifting wavelet transforms that contains rounding-off arithmetic for mapping integers to integers. The lifting term contains parameters that are learned by using standard training images of targets. We assume that the targets include many high frequency components. In order to obtain the features of the targets the lifting parameters are determined by a condition that high frequency components are vanished in wavelet transform. But the condition cannot be determined by the parameters wholly. So we put an additional condition of minimizing the squared sum of the lifting parameters. The advantage of using integer-type wavelet transform is simple and robust to noise. Simulation illustrated the approach can detect and track the moving targets in dim background. We would test our algorithm in the TV tracking system.

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