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Adriano Mancini, Francesco Solfanelli, Luca Coviello, Francesco Maria Martini, Serena Mandolesi and Raffaele Zanoli
Yield prediction is a crucial activity in scheduling agronomic operations and in informing the management and financial decisions of a wide range of stakeholders of the organic durum wheat supply chain. This research aims to develop a yield forecasting s...
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Andreas Pester, Yevgeniya Sulema, Ivan Dychka and Olga Sulema
In many tasks related to an object?s observation or real-time monitoring, the gathering of temporal multimodal data is required. Such data sets are semantically connected as they reflect different aspects of the same object. However, data sets of differe...
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Yicong Li, Tong Zhang, Xiaofei Lv, Yingxi Lu and Wangshu Wang
It is important to capture passengers? public transit behavior and their mobility to create profiles, which are critical for analyzing human activities, understanding the social and economic structure of cities, improving public transportation, assisting...
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Junbo Yu, Tinghua Ai, Haijiang Xu, Lingrui Yan and Yilang Shen
The consistency of geospatial data is of great significance for the application and updating of geographic information in web maps. Due to the multiple data sources and different temporal versions, the tile web maps usually meet the inconsistency questio...
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Zhenwen He, Chi Zhang and Yunhui Cheng
Time series data typically exhibit high dimensionality and complexity, necessitating the use of specific approximation methods to perform computations on the data. The currently employed compression methods suffer from varying degrees of feature loss, le...
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Miao Tian, Xinxin Hu, Jiakai Huang, Kai Ma, Haiyan Li, Shuai Zheng, Liufeng Tao and Qinjun Qiu
The growing proliferation of geographic information presents a substantial challenge to the traditional framework of a geographic information analysis and service. The dynamic integration and representation of geographic knowledge, such as triples, with ...
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Yubo Zheng, Yingying Luo, Hengyi Shao, Lin Zhang and Lei Li
Contrastive learning, as an unsupervised technique, has emerged as a prominent method in time series representation learning tasks, serving as a viable solution to the scarcity of annotated data. However, the application of data augmentation methods duri...
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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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Chao Liu, Buhong Wang, Zhen Wang, Jiwei Tian, Peng Luo and Yong Yang
With the development of the air traffic management system (ATM), the cyber threat for ATM is becoming more and more serious. The recognition of ATM cyber threat entities is an important task, which can help ATM security experts quickly and accurately rec...
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Nanyu Chen, Anran Yang, Luo Chen, Wei Xiong and Ning Jing
Spatio-temporal association analysis has attracted attention in various fields, such as urban computing and crime analysis. The proliferation of positioning technology and location-based services has facilitated the expansion of association analysis acro...
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