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    Cameras Can Record Object Density More Accurately with New Crowd-Counting Approach

    Article obtained from Photonics RSS Feed.

    Crowd counting — the process of obtaining information on the density or number of objects such as vehicles or people — can benefit from the same deep learning techniques that have been used for image and video processing. Scientists at Japan Advanced Institute of Science and Technology (JAIST), in collaboration with researchers at Sirindhorn International Institute of Technology (SIIT) in Thailand, developed a way to achieve higher performance in crowd counting by using a backward connection in a deep neural network (DNN).

    The estimation network proposed by the researchers consists of two identical networks for extracting a high-level feature and estimating the final result. To preserve semantic information, dilated…

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    Jul, 29 2020 |

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