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Titlebook: Computer Analysis of Images and Patterns; 17th International C Michael Felsberg,Anders Heyden,Norbert Krüger Conference proceedings 2017 Sp

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楼主: 武士精神
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Deep Objective Image Quality Assessmentmeters of these operations (e.g. JPEG compression quality). For this purpose, we propose a CNN architecture for multi-label classification and integrate patch predictions to obtain continuous parameter estimates. We train this architecture using softmax layers that support multi-label classification
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Stacked Progressive Auto-Encoders for Clothing-Invariant Gait Recognition such as view angles, clothing, and carrying condition can alter an individual’s gait pattern. These variations make the task of gait analysis much more complicated. Recognizing different subjects under clothing variations remains one of the most challenging tasks in gait recognition. In this paper,
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Functionals of the Brownian Bridge As a result, we observe that the directional dominance score and the improvement rate in noise reduction performance are correlated. Therefore, the resulting score can be used to estimate the performance of DTV method.
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Link Prediction in Social Networksmated with high accuracy. Furthermore, we demonstrate that the learned features are discriminative for subjective image quality assessment, achieving state-of-the-art results on the LIVE2 dataset via transfer learning. The proposed CNN architecture supports any multi-label classification problem.
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