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An adaptive representation algorithm for Multi-scale logo detection
Displays, 2021Abstract The proliferation of logo has driven research into multiple applications, like logo duration monitoring in advertising videos and logo infringement detection. Recently, logo research has attracted a rapt attention and keen interest from researchers.
Ye Meng +5 more
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Edge detection with multi-scale representation and refined Network
IET Conference Proceedings, 2022Edge detection is a representation of boundaries between objects and regions in an image. Due to the variations of types, scales, intensities as well as background, the detection of these boundaries represents a challenge for different computer vision algorithms.
Elharrouss, Omar +3 more
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Graph embedding via multi-scale graph representations
Information Sciences, 2021Abstract Graph embedding provides an effective way to encode graph nodes as continuous vector representations in a low-dimensional space. The high-order proximities based graph embedding methods can preserve global structures, but the high-order proximities based objectives typically imply non-convex optimization and high computational ...
Yu Xie 0009 +4 more
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Multi-Scale Deep Representation Aggregation for Vein Recognition
IEEE Transactions on Information Forensics and Security, 2021The recent success of Deep Convolutional Neural Network (DCNN) for various computer vision tasks such as image recognition has already demonstrated its robust feature representation ability. However, the limitation of training database on small scale vein recognition tasks restricts its performance because the recognition result of DCNN depends heavily
Jihong Zhu, Jun Wang, Guoqing Wang
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Representation of image content with multi-scale segmentation
2013 International Conference on Machine Learning and Cybernetics, 2013Representation of image content is an important part of image annotation and retrieval, which has become a hot topic in computer vision recently. In order to represent image content more efficiently and accurately, grid based methods such as bag-of-words, were proposed and attracted more attention.
Jing Zhang 0041 +4 more
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Multi-scale Representation and Persistency for Shape Description
2008Extraction, organization and exploitation of topological features are emerging topics in computer vision and graphics. However, such kind of features often exhibits weak robustness with respect to small perturbations and it is often unclear how to distinguish truly topological features from topological noise.
Moroni D, Salvetti M, Salvetti O
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Multi-scale representation of tribological surfaces
Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 2002Many numerical surface topography analysis methods exist today. However, even for the moderately complicated topography of a tribological surface these methods can provide only limited information. The reason is that tribological surfaces often exhibit a non-stationary and multi-scale nature while the numerical methods currently used work well with ...
P Podsiadlo, G. W. Stachowiak
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Multi-scale representations of the motion trajectory
SPIE Proceedings, 2007At present, mobile computation is developing rapidly for location-based services. For the online GIS or cartography of moving objects, the techniques of progressively refined details greatly reduce the overhead of storage, computation, display, and communication resources.
Hong Shu, Jun Pang, Cuihong Qi
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Multi-Scale Representation of a Digital Line
Cartography and Geographic Information Systems, 1996A scheme for multi-scale geometrical representation of a digital line is proposed. A digital line is represented as a structured object in which lines at different levels of resolution are represented as lists, quadcodes are used as control mechanism for guiding line simplification at multiple scales of a pyramid, and operators for simplification and ...
Benjamin F. Zhan, Barbara P. Buttenfield
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Multi-scale pyramid pooling for deep convolutional representation
2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2015Compared to image representation based on low-level local descriptors, deep neural activations of Convolutional Neural Networks (CNNs) are richer in mid-level representation, but poorer in geometric invariance properties. In this paper, we present a straightforward framework for better image representation by combining the two approaches.
Donggeun Yoo +3 more
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