Results 11 to 20 of about 6,693,779 (355)
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features [PDF]
IEEE International Conference on Computer Vision, 2021 Image Retrieval is a fundamental task of obtaining images similar to the query one from a database. A common image retrieval practice is to firstly retrieve candidate images via similarity search using global image features and then re-rank the ...
Min Yang +7 more
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Journal of Imaging, 2022 Color texture classification aims to recognize patterns by the analysis of their colors and their textures. This process requires using descriptors to represent and discriminate the different texture classes.
Mohamed Alimoussa +4 more
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Feature Transformation for Defending Adversarial Attack on Image Retrieval [PDF]
Jisuanji kexue, 2021 The adversarial attack is firstly studied in image classification to generate imperceptible perturbations that can mislead the prediction of a convolutional neural network.Recently,it has also been extensively explored in image retrieval and shows that ...
XU Xing, SUN Jia-liang, WANG Zheng, YANG Yang
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Progressive Learning for Image Retrieval with Hybrid-Modality Queries [PDF]
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022 Image retrieval with hybrid-modality queries, also known as composing text and image for image retrieval (CTI-IR), is a retrieval task where the search intention is expressed in a more complex query format, involving both vision and text modalities.
Yida Zhao, Yuqing Song, Qin Jin
semanticscholar +1 more source
Information, 2022 With the continuous progress of image retrieval technology, in the field of image retrieval, the speed of a search for a desired image from a great deal of image data becomes a hot issue. Convolutional Neural Networks (CNN) have been used in the field of
Youmeng Luo +3 more
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Boosting image retrieval [PDF]
Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), 2002 We present an approach for image retrieval using a very large number of highly selective features and efficient online learning. Our approach is predicated on the assumption that each image is generated by a sparse set of visual "causes" and that images which are visually similar share causes. We propose a mechanism for computing a very large number of
Kinh Tieu, Paul Viola
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Conditioned and composed image retrieval combining and partially fine-tuning CLIP-based features
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 In this paper, we present an approach for conditioned and composed image retrieval based on CLIP features. In this extension of content-based image retrieval (CBIR) an image is combined with a text that provides information regarding user intentions, and
Alberto Baldrati +3 more
semanticscholar +1 more source
Effective conditioned and composed image retrieval combining CLIP-based features
Computer Vision and Pattern Recognition, 2022 Conditioned and composed image retrieval extend CBIR systems by combining a query image with an additional text that expresses the intent of the user, describing additional requests w.r.t. the visual content of the query image.
Alberto Baldrati +3 more
semanticscholar +1 more source
A Probabilistic Analysis of Sparse Coded Feature Pooling and Its Application for Image Retrieval. [PDF]
PLoS ONE, 2015 Feature coding and pooling as a key component of image retrieval have been widely studied over the past several years. Recently sparse coding with max-pooling is regarded as the state-of-the-art for image classification. However there is no comprehensive
Yunchao Zhang +3 more
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Application of Ontologies in Information Retrieval of Digital Collections with Emphasis on Images [PDF]
بازیابی دانش و نظامهای معنایی, 2022 The purpose of this study is to use ontologies in the information retrieval of digital collections with an emphasis on images. The present research is of applied type and has been done by library method and systematic review of resources with an ...
Ahmadreza Ahmadi Mirghaed +2 more
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