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Topical Meeting On Signal Recovery and Synthesis II, 1986
In this review an overview will be given of the state-of-the-art in phase retrieval (PR). PR occurs in many different areas of signal processing: - in imaging, where the image only yields the modulus of the wavefunction in the image plane, while for the reconstruction of the object we also need its phase - in speckle interferometry where we obtain the ...
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In this review an overview will be given of the state-of-the-art in phase retrieval (PR). PR occurs in many different areas of signal processing: - in imaging, where the image only yields the modulus of the wavefunction in the image plane, while for the reconstruction of the object we also need its phase - in speckle interferometry where we obtain the ...
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2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005
We present a comprehensive strategy for evaluating image retrieval algorithms. Because automated image retrieval is only meaningful in its service to people, performance characterization must be grounded in human evaluation. Thus we have collected a large data set of human evaluations of retrieval results, both for query by image example and query by ...
N.V. Shirahatti, K. Barnard
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We present a comprehensive strategy for evaluating image retrieval algorithms. Because automated image retrieval is only meaningful in its service to people, performance characterization must be grounded in human evaluation. Thus we have collected a large data set of human evaluations of retrieval results, both for query by image example and query by ...
N.V. Shirahatti, K. Barnard
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SOLAR: Second-Order Loss and Attention for Image Retrieval
European Conference on Computer Vision, 2020Recent works in deep-learning have shown that second-order information is beneficial in many computer-vision tasks. Second-order information can be enforced both in the spatial context and the abstract feature dimensions.
Tony Ng +3 more
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Scalable Deep Hashing for Large-Scale Social Image Retrieval
IEEE Transactions on Image Processing, 2020Recent years have witnessed the wide application of hashing for large-scale image retrieval, because of its high computation efficiency and low storage cost. Particularly, benefiting from current advances in deep learning, supervised deep hashing methods
Hui Cui +4 more
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Enhancing Sketch-Based Image Retrieval by CNN Semantic Re-ranking
IEEE Transactions on Cybernetics, 2020This paper introduces a convolutional neural network (CNN) semantic re-ranking system to enhance the performance of sketch-based image retrieval (SBIR).
Luo Wang +4 more
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Proceedings of the 4th workshop on Patent information retrieval, 2011
Drawings are an important component of patents, and many search tasks in the intellectual property domain rely on the comparison of patent drawings. In this paper, we begin with a review of algorithms developed for the automated retrieval of similar images in the patent domain.
Allan Hanbury +3 more
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Drawings are an important component of patents, and many search tasks in the intellectual property domain rely on the comparison of patent drawings. In this paper, we begin with a review of algorithms developed for the automated retrieval of similar images in the patent domain.
Allan Hanbury +3 more
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Proceedings. IEEE Workshop on Content-Based Access of Image and Video Libraries (Cat. No.98EX173), 2002
One of the most significant problems in content-based image retrieval results from the lack of a common test-bed for researchers. Although many published articles report on content-based retrieval results using color photographs, there has been little effort in establishing a benchmark set of images and queries.
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One of the most significant problems in content-based image retrieval results from the lack of a common test-bed for researchers. Although many published articles report on content-based retrieval results using color photographs, there has been little effort in establishing a benchmark set of images and queries.
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2012
In this technical demonstration we present a content-based image retrieval system based on the 'query by example' paradigm. The system effectiveness will be proved for both category and target search on two standard image databases, even without a "good" initial example and ancillary information, such as device metadata, text annotations, etc.
CIOCCA, GIANLUIGI +3 more
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In this technical demonstration we present a content-based image retrieval system based on the 'query by example' paradigm. The system effectiveness will be proved for both category and target search on two standard image databases, even without a "good" initial example and ancillary information, such as device metadata, text annotations, etc.
CIOCCA, GIANLUIGI +3 more
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Deep Image Retrieval: Learning Global Representations for Image Search
European Conference on Computer Vision, 2016We propose a novel approach for instance-level image retrieval. It produces a global and compact fixed-length representation for each image by aggregating many region-wise descriptors.
Albert Gordo +3 more
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Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries, 2008
We consider the task of automatic slide image retrieval, in which slide images are ranked for relevance against a textual query. Our implemented system, SLIDIR caters specifically for this task using features specifically designed for synthetic images embedded within slide presentation. We show promising results in both the ranking and binary relevance
Guo Min Liew, Min-Yen Kan
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We consider the task of automatic slide image retrieval, in which slide images are ranked for relevance against a textual query. Our implemented system, SLIDIR caters specifically for this task using features specifically designed for synthetic images embedded within slide presentation. We show promising results in both the ranking and binary relevance
Guo Min Liew, Min-Yen Kan
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