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Jieyu Liang, Chao Ren, Yi Li, Weiting Yue, Zhenkui Wei, Xiaohui Song, Xudong Zhang, Anchao Yin and Xiaoqi Lin
Normalized difference vegetation index (NDVI) time series data, derived from optical images, play a crucial role for crop mapping and growth monitoring. Nevertheless, optical images frequently exhibit spatial and temporal discontinuities due to cloudy an...
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Xihou Zhang, Dingding Han, Xiaobo Zhang and Leheng Fang
The increasing urban traffic problems have made the transportation system require a large amount of data. Aiming at the current problems of data types redundancy and low coordination rate of intelligent transportation systems (ITS), this paper proposes a...
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Ahmed J. Obaid and Hassanain K. Alrammahi
Recognizing facial expressions plays a crucial role in various multimedia applications, such as human?computer interactions and the functioning of autonomous vehicles. This paper introduces a hybrid feature extraction network model to bolster the discrim...
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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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Jeba Nadarajan and Rathi Sivanraj
Periodic traffic prediction and analysis is essential for urbanisation and intelligent transportation systems (ITS). However, traffic prediction is challenging due to the nonlinear flow of traffic and its interdependencies on spatiotemporal features. Tra...
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Qingmei Li, Xin Chen, Xiaochong Tong, Xuantong Zhang and Chengqi Cheng
In order to cope with the rapid growth of spatiotemporal big data, data organization models based on discrete global grid systems have developed rapidly in recent years. Due to the differences in model construction methods, grid level subdivision and cod...
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Zichao He, Chunna Zhao and Yaqun Huang
Multivariate time series forecasting has long been a subject of great concern. For example, there are many valuable applications in forecasting electricity consumption, solar power generation, traffic congestion, finance, and so on. Accurately forecastin...
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Yangnan Guo, Cangjiao Wang, Shaogang Lei, Junzhe Yang and Yibo Zhao
Spatio-temporal fusion algorithms dramatically enhance the application of the Landsat time series. However, each spatio-temporal fusion algorithm has its pros and cons of heterogeneous land cover performance, the minimal number of input image pairs, and ...
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Qian Xue and Wei Song
Climatic changes significantly impact the socio-economic system. Compared with research on the impacts of climate change on the agricultural economic system, researches on the impacts on the industrial economic system are still scarce. This is mainly bec...
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