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Titlebook: Human-Centered Social Media Analytics; Yun Fu Book 2014 Springer International Publishing Switzerland 2014 Age Estimation.Big Data.Compute

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21#
發(fā)表于 2025-3-25 04:17:17 | 只看該作者
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發(fā)表于 2025-3-25 09:21:18 | 只看該作者
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發(fā)表于 2025-3-25 14:11:13 | 只看該作者
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發(fā)表于 2025-3-25 16:20:20 | 只看該作者
Social Role Recognition for Human Event Understandingole annotations, and introduce annotations on a subset of videos from the TRECVID-MED11 event kits for evaluation purposes. The performance of the model is compared against different baseline methods on these datasets.
25#
發(fā)表于 2025-3-25 22:28:10 | 只看該作者
Facial Age Estimation: A Data Representation Perspectivein time order, by constructing a representative subspace. The second solution is based on a new learning paradigm named label distribution learning, which mainly manipulates the right side of the mapping. The basic idea is to regard each face image as an instance associated with a label distribution which covers a certain number of age labels.
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發(fā)表于 2025-3-26 03:04:40 | 只看該作者
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發(fā)表于 2025-3-26 04:28:51 | 只看該作者
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發(fā)表于 2025-3-26 09:17:49 | 只看該作者
Learning Social Relations from Videos: Features, Models, and Analytics In this chapter, we review one of the ?rst studies towards learning such relations from videos using visual and auditory cues. The main contribution can be stated as the association of low-level video features to social relations by machine learning methodology. Specifically, support vector regress
29#
發(fā)表于 2025-3-26 15:22:30 | 只看該作者
30#
發(fā)表于 2025-3-26 20:48:42 | 只看該作者
Social Role Recognition for Human Event Understandingntal component of human event description. We focus on a weakly supervised setting, where we are provided with different videos belonging to an event class, without training role labels. Since social roles are described by the interaction between people in an event, we propose a Conditional Random F
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