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CONTENT BASED IMAGE RETRIEVAL SYSTEM BY FUSION OF COLOR, TEXTURE AND EDGE FEATURES WITH SVM CLASSIFIER AND RELEVANCE FEEDBACK

机译：基于内容的图像检索系统通过融合颜色，纹理和边缘特征，具有SVM分类器和相关性反馈

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作者
Priyanka Saxena;
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年度 2018
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专利

1. Convolutional neural networks for relevance feedback in content based image retrieval A Content based image retrieval system that exploits convolutional neural networks both for feature extraction and for relevance feedback [J] . Lorenzo Putzu, Luca Piras, Giorgio Giacinto Multimedia Tools and Applications . 2020,第37a38期

机译：基于内容的图像检索的相关反馈的卷积神经网络基于内容的图像检索系统，用于利用特征提取和相关性反馈的卷积神经网络
2. A new integrated SVM classifiers for relevance feedback content-based image retrieval using EM parameter estimation [J] . Xiang-Yang Wang, Jing-Wei Chen, Hong-Ying Yang Applied Soft Computing . 2011,第2期

机译：一种新的集成SVM分类器，用于使用EM参数估计进行基于相关性反馈的基于内容的图像检索
3. Content based image retrieval based on weighted fusion of texture and color features derived from modified local binary patterns and local neighborhood difference patterns [J] . Kayhan Nasim, Fekri-Ershad Shervan Multimedia Tools and Applications . 2021,第21a23期

机译：基于修改的局部二进制模式的纹理和颜色特征的加权融合的基于内容的图像检索和局部邻域差异模式
4. Content-Based Remote Sensing Image Retrieval Using Image Multi-feature Combination and SVM-Based Relevance Feedback [C] . Lijun Zhao, Jiakui Tang, Xinju Yu, World congress on computer science and information engineering;CSIE 2011 . 2011

机译：基于图像多特征组合和基于SVM的相关性反馈的基于内容的遥感图像检索
5. Local feature saliency maps for persistent relevance feedback-driven content-based image retrieval. [D] . Jones, Brett Charles. 2001

机译：局部特征显着图，用于持久性相关性反馈驱动的基于内容的图像检索。
6. An Efficient Method for Brain Tumor Detection Using Texture Features and SVM Classifier in MR Images [O] . Kavin Kumar K, Meera Devi T, Maheswaran S 2018

机译：利用纹理特征和SVM分类器在MR图像中进行脑肿瘤检测的有效方法
7. Use of Color Feature Extraction Technique based on Color Distribution and Relevance Feedback for Content based Image Retrieval [O] . Sandip S. Patil, Atul V. Dusane 2013

机译：基于颜色分布和相关反馈的颜色特征提取技术在基于内容的图像检索中的应用

CONTENT BASED IMAGE RETRIEVAL SYSTEM BY FUSION OF COLOR, TEXTURE AND EDGE FEATURES WITH SVM CLASSIFIER AND RELEVANCE FEEDBACK

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