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Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co...
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Karly S. Franz, Grace Reszetnik and Tom Chau
Brushstroke segmentation algorithms are critical in computer-based analysis of fine motor control via handwriting, drawing, or tracing tasks. Current segmentation approaches typically rely only on one type of feature, either spatial, temporal, kinematic,...
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Yafei Xi, Quanhua Hou, Yaqiong Duan, Kexin Lei, Yan Wu and Qianyu Cheng
Exploring the correlation of the built environment with metro ridership is vital for fostering sustainable urban growth. Although the research conducted in the past has explored how ridership is nonlinearly influenced by the built environment, less resea...
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Xie Lian, Xiaolong Hu, Liangsheng Shi, Jinhua Shao, Jiang Bian and Yuanlai Cui
The parameters of the GR4J-CemaNeige coupling model (GR4neige) are typically treated as constants. However, the maximum capacity of the production store (parX1) exhibits time-varying characteristics due to climate variability and vegetation coverage chan...
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Ali Uzunlar and Muhammet Omer Dis
The hydrological cycle should be scrutinized and investigated under recent climate change scenarios to ensure global water management and to increase its utilization. Although the FAO proposed the use of the Penman?Monteith (PM) equation worldwide to pre...
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Longxin Yao, Yun Lu, Mingjiang Wang, Yukun Qian and Heng Li
The construction of complex networks from electroencephalography (EEG) proves to be an effective method for representing emotion patterns in affection computing as it offers rich spatiotemporal EEG features associated with brain emotions. In this paper, ...
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Shukai Li, Xiaofang Wang, Dongri Shan and Peng Zhang
Temporal modeling is a key problem in action recognition, and it remains difficult to accurately model temporal information of videos. In this paper, we present a local spatiotemporal extraction module (LSTE) and a channel time excitation module (CTE), w...
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Dapeng Jiang, Guoyou Shi, Na Li, Lin Ma, Weifeng Li and Jiahui Shi
In the context of the rapid development of deep learning theory, predicting future motion states based on time series sequence data of ship trajectories can significantly improve the safety of the traffic environment. Considering the spatiotemporal corre...
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Manar M. F. Donia, Wessam H. El-Behaidy and Aliaa A. A. Youssif
The study of human behaviors aims to gain a deeper perception of stimuli that control decision making. To describe, explain, predict, and control behavior, human behavior can be classified as either non-aggressive or anomalous behavior. Anomalous behavio...
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Qingyong Zhang, Lingfeng Zhou, Yixin Su, Huiwen Xia and Bingrong Xu
Considering the spatial and temporal correlation of traffic flow data is essential to improve the accuracy of traffic flow prediction. This paper proposes a traffic flow prediction model named Dual Spatial Convolution Gated Recurrent Unit (DSC-GRU). In p...
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