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Densely Connected Convolutional Networks With Attention LSTM for Crowd Flows Prediction

机译：密集地连接卷积网络，因为人群流动预测的LSTM

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Wei Li; Wei Tao; Junyang Qiu; Xin Liu; Xingyu Zhou; Zhisong Pan;
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年度 2019
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1. Minkowski Sommon Feature Map-based Densely Connected Deep Convolution Network with LSTM for academic performance prediction [J] . Ramanathan Kaviyarasi, Thangavel Balasubramanian Concurrency and computation: practice and experience . 2021,第13期

机译：Minkowski Modmon具有基于地图的密集连接的深度卷积网络，具有LSTM，用于学术性能预测
2. Deep spatial-temporal networks for crowd flows prediction by dilated convolutions and region-shifting attention mechanism [J] . Tian Chujie, Zhu Xinning, Hu Zheng, Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies . 2020,第10期

机译：用于人群流量的深度空间网络通过扩张卷积和区域移位注意力的预测
3. Human action recognition using convolutional LSTM and fully-connected LSTM with different attentions [J] . Zhang Zufan, Lv Zongming, Gan Chenquan, Neurocomputing . 2020,第Octa14期

机译：使用卷积LSTM和完全连接的LSTM具有不同关注的人类行动识别
4. ST-DCN: A Spatial-Temporal Densely Connected Networks for Crowd Flow Prediction [C] . Longlong Xu, Xiansheng Chen, Yue Xu, Aisa-Pacific web and web-age information management joint conference on web and big data . 2019

机译：ST-DCN：时空密集连接网络，用于人群流量预测
5. Interactive Tracking, Prediction, and Behavior Learning of Pedestrians in Dense Crowds [D] . Bera, Aniket. 2017

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6. Skin Lesion Classification Using Densely Connected Convolutional Networks with Attention Residual Learning [O] . Jing Wu, Wei Hu, Yuan Wen, 2020

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7. Non-Local Attention and Densely-Connected Convolutional Neural Networks for Malignancy Suspiciousness Classification of Gastric Ulcer [O] . Muyi Sun, Kaiyi Liang, Wenbao Zhang, 2020

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Densely Connected Convolutional Networks With Attention LSTM for Crowd Flows Prediction

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