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2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Convolutional Neural Networks (CNNs) became a very popular tool for image analysis. Convolutions are fast to compute and easy to store, but they also have some limitations. First, they are shift-invariant and, as a result, they do not adapt to different regions of the image.
Irina Shevlev, Shai Avidan
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Convolutional Neural Networks (CNNs) became a very popular tool for image analysis. Convolutions are fast to compute and easy to store, but they also have some limitations. First, they are shift-invariant and, as a result, they do not adapt to different regions of the image.
Irina Shevlev, Shai Avidan
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Parasomnias: co-occurrence and genetics
Psychiatric Genetics, 2001In clinical practice, parasomnias are often found to run in families and to co-occur. Several studies have indicated a role of genetic factors in them. In 1990, a questionnaire (response rate, 77%) sent to the Finnish Twin Cohort, a representative population sample aged 33-60 years, surveyed the frequency of five parasomnias (sleepwalking, sleeptalking,
C, Hublin +3 more
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Spatiotemporal Co-occurrence Rules
2014Spatiotemporal co-occurrence rules (STCORs) discovery is an important problem in many application domains such as weather monitoring and solar physics, which is our application focus. In this paper, we present a general framework to identify STCORs for continuously evolving spatiotemporal events that have extended spatial representations.
Karthik Ganesan Pillai +4 more
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Using Tag Co-occurrence for Recommendation
2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009Tagging with free form tags is becoming an increasingly important indexing mechanism. However, free form tags have characteristics that require special treatment when used for searching or recommendation because they show much more variation than controlled keywords. In this paper we present a method that puts this large variation to good use.
Christian Wartena +2 more
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2014
Since 80% of all information in the World Wide Web (WWW) is in textual form, most of the search activities of the users are based on groups of search words forming queries that represent their information needs. The quality of the returned results -usually evaluated using measures such as precision and recall- mostly depends on the quality of the ...
Mario Kubek, Herwig Unger
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Since 80% of all information in the World Wide Web (WWW) is in textual form, most of the search activities of the users are based on groups of search words forming queries that represent their information needs. The quality of the returned results -usually evaluated using measures such as precision and recall- mostly depends on the quality of the ...
Mario Kubek, Herwig Unger
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Co-occurrence flow for pedestrian detection
2011 18th IEEE International Conference on Image Processing, 2011The last few years have seen considerable progress in pedestrian detection. Recent work has established a combination of oriented gradients and optic flow as effective features although the detection rates are still unsatisfactory for practical use. This paper introduces a new type of motion feature, the co-occurrence flow (CoF).
Atsuto Maki +3 more
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Euclidean embedding of co-occurrence data
J. Mach. Learn. Res., 2007Summary: Embedding algorithms search for a low dimensional continuous representation of data, but most algorithms only handle objects of a single type for which pairwise distances are specified. This paper describes a method for embedding objects of different types, such as images and text, into a single common Euclidean space, based on their co ...
Amir Globerson +3 more
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Co-Occurrent Features in Semantic Segmentation
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019Recent work has achieved great success in utilizing global contextual information for semantic segmentation, including increasing the receptive field and aggregating pyramid feature representations. In this paper, we go beyond global context and explore the fine-grained representation using co-occurrent features by introducing Co-occurrent Feature ...
Hang Zhang 0005 +3 more
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Proceedings of the Workshop on Use of Context in Vision Processing, 2009
Head pose and gesture offer several conversational grounding cues and are used extensively in face-to-face interaction among people. To accurately recognize visual feedback, humans often use contextual knowledge from previous and current events to anticipate when feedback is most likely to occur.
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Head pose and gesture offer several conversational grounding cues and are used extensively in face-to-face interaction among people. To accurately recognize visual feedback, humans often use contextual knowledge from previous and current events to anticipate when feedback is most likely to occur.
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Co-occurrence analysis of speech waveforms
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985The co-occurrence matrix, a two-dimensional histogram of pairs of sample amplitudes, is explored as a representation of the digital speech waveform. Co-occurrence matrix representations support a hypothesis-testing approach to digital speech analysis. This approach is pursued in the formulation of a quantitative (chi-square) measure of sample amplitude
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