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Large-scale Video Classification with Convolutional Neural ...
Large-scale Video Classification with Convolutional Neural Networks Andrej Karpathy1,2 George Toderici1 Sanketh Shetty1. 1 1. Thomas Leung Rahul Sukthankar Li Fei-Fei2. 1 2. Google Research Computer Science Department, Stanford University Abstract image features [28]. Encouraged by positive results in do- main of images, we study the performance of CNNs in Convolutional Neural Networks (CNNs) have been es- Large-scale Video Classification , where the networks have tablished as a powerful class of models for image recog- access to not only the appearance information present in nition problems. Encouraged by these results, we pro- single, static images, but also their complex temporal evolu- vide an extensive empirical evaluation of CNNs on large - tion. There are several challenges to extending and applying scale Video Classification using a new dataset of 1 million CNNs in this setting. YouTube videos belonging to 487 classes.
cently, Convolutional Neural Networks (CNNs) [15] have been demonstrated as an effective class of models for un-derstanding image content, giving state-of-the-art results on image recognition, segmentation, detection and retrieval [11,3,2,20,9,18]. The key enabling factors behind these results were techniques for scaling up the networks to tens
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