Results 211 to 220 of about 699,270 (266)
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Deep Variational and Structural Hashing
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020In this paper, we propose a deep variational and structural hashing (DVStH) method to learn compact binary codes for multimedia retrieval. Unlike most existing deep hashing methods which use a series of convolution and fully-connected layers to learn binary features, we develop a probabilistic framework to infer latent feature representation inside the
Venice Erin Liong +3 more
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2013
The discrete scale space representation L of f is continuous in scale t. A computational investigation of L however must rely on a finite number of sampled scales. There are multiple approaches to sampling L differing in accuracy, runtime complexity and memory usage.
Martin Tschirsich, Arjan Kuijper
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The discrete scale space representation L of f is continuous in scale t. A computational investigation of L however must rely on a finite number of sampled scales. There are multiple approaches to sampling L differing in accuracy, runtime complexity and memory usage.
Martin Tschirsich, Arjan Kuijper
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IEEE Internet Computing, 2002
Our current understanding of Web structure is based on large graphs created by centralized crawlers and indexers. They obtain data almost exclusively from the so-called surface Web, which consists, loosely speaking, of interlinked HTML pages. The deep Web, by contrast, is information that is reachable over the Web, but that resides in databases; it is ...
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Our current understanding of Web structure is based on large graphs created by centralized crawlers and indexers. They obtain data almost exclusively from the so-called surface Web, which consists, loosely speaking, of interlinked HTML pages. The deep Web, by contrast, is information that is reachable over the Web, but that resides in databases; it is ...
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The deep structure of continents
Reviews of Geophysics, 1963Gravity and heat flow observations demonstrate that, on the average, mass and radioactivity per unit area are equal under continents and oceans. A global representation of the anomalies in the heat flow and gravity fields shows many similarities, and horizontal gradients in both fields are correlated with earthquake zones.
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Deep Structural Contour Detection
Proceedings of the 28th ACM International Conference on Multimedia, 2020Object contour detection is the fundamental and preprocessing step for multimedia applications such as icon generation, object segmentation, and tracking. The quality of contour prediction is of great importance in these applications since it affects the subsequent process. In this work, we aim to develop a high-performance contour detection system. We
Ruoxi Deng, Shengjun Liu 0002
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Proceedings of the AAAI Conference on Artificial Intelligence, 2023
In the scene of self-supervised graph learning, Mutual Information (MI) was recently introduced for graph encoding to generate robust node embeddings. A successful representative is Deep Graph Infomax (DGI), which essentially operates on the space of node features but ignores topological structures, and just considers global graph summary.
Wenting Zhao 0001 +5 more
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In the scene of self-supervised graph learning, Mutual Information (MI) was recently introduced for graph encoding to generate robust node embeddings. A successful representative is Deep Graph Infomax (DGI), which essentially operates on the space of node features but ignores topological structures, and just considers global graph summary.
Wenting Zhao 0001 +5 more
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On the deep structure of information systems
Information Systems Journal, 1995Abstract. The deep structure of an information system comprises those properties that manifest the meaning of the real‐world system the information system is intended to model. In this paper we describe three models we have developed of information systems' deep‐structure properties.
Wand, Yair, Weber, Ron
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