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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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Lin Mu, Haiwen Tu, Xiongfei Geng, Fangli Qiao, Zhihui Chen, Sen Jia, Ruifei Zhu, Tianyu Zhang and Zhi Chen
Annually, hundreds of individuals tragically lose their lives at sea due to shipwrecks or aircraft accidents. For search and rescue personnel, the task of locating the debris of a downed aircraft in the vastness of the ocean presents a formidable challen...
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Haohan Shi, Xiyu Shi and Safak Dogan
Audio inpainting plays an important role in addressing incomplete, damaged, or missing audio signals, contributing to improved quality of service and overall user experience in multimedia communications over the Internet and mobile networks. This paper p...
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Grace-Mercure Bakanina Kissanga, Hasan Zulfiqar, Shenghan Gao, Sophyani Banaamwini Yussif, Biffon Manyura Momanyi, Lin Ning, Hao Lin and Cheng-Bing Huang
Accurate prediction of subcellular localization of viral proteins is crucial for understanding their functions and developing effective antiviral drugs. However, this task poses a significant challenge, especially when relying on expensive and time-consu...
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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Stanislav Letkovský, Sylvia Jencová and Petra Va?anicová
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial in...
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Sajjad E. Rasheed, Duaa Al-Jeznawi, Musab Aied Qissab Al-Janabi and Luís Filipe Almeida Bernardo
The structural stability of pipe pile foundations under seismic loading stands as a critical concern, demanding an accurate assessment of the maximum settlement. Traditionally, this task has been addressed through complex numerical modeling, accounting f...
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Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction...
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Xiaobing Xu and Yaping Zhang
Running posture estimation is a specialized task in human pose estimation that has received relatively little research attention due to the lack of appropriate datasets. To address this issue, this paper presents the construction of a new benchmark datas...
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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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