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Deep Learning (DL) has been proven as a powerful recognition method as evidenced by its success in recent computer vision competitions. The most accurate results have been obtained by ensembles of DL models that pool their results. However, such ensembles are computationally costly, making them inapplicable to real-time applications. In this paper, we apply model compression techniques to the problem...
Despite significant progress in the development of human action detection datasets and algorithms, no current dataset is representative of real-world aerial view scenarios. We present Okutama-Action, a new video dataset for aerial view concurrent human action detection. It consists of 43 minute-long fully-annotated sequences with 12 action classes. Okutama-Action features many challenges missing in...
It will not take a longtime that the human will apply the networks of sensors in controlling the environment and predict natural disasters. This vast function would create bulks of sensor data to be applied World Wide Web. These bulks of data should be handled and processed a primary manner, which is a difficult task; therefore only the expert in this field can process them. One solution to overcome...
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