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Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
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Ivan A. Hernandez-Robles, Xiomara Gonzalez-Ramirez, Juan C. Olivares-Galvan, Rafael Escarela-Perez and Rodrigo Ocon-Valdez
Designing and manufacturing transformers often involves variations in heights and thicknesses of windings. However, such geometric asymmetry introduces a significant impact on the magnitude of stray transformer losses. This study examines the effects of ...
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Hexin Lu, Xiaodong Zhu, Jingwei Cui and Haifeng Jiang
The process of iris recognition can result in a decline in recognition performance when the resolution of the iris images is insufficient. In this study, a super-resolution model for iris images, namely SwinGIris, which combines the Swin Transformer and ...
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Zhichao Chen, Guoqiang Wang, Tao Lv and Xu Zhang
Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergenc...
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Utpal Barman, Parismita Sarma, Mirzanur Rahman, Vaskar Deka, Swati Lahkar, Vaishali Sharma and Manob Jyoti Saikia
Invading pests and diseases always degrade the quality and quantity of plants. Early and accurate identification of plant diseases is critical for plant health and growth. This work proposes a smartphone-based solution using a Vision Transformer (ViT) mo...
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Hamed Alshammari, Ahmed El-Sayed and Khaled Elleithy
The effectiveness of existing AI detectors is notably hampered when processing Arabic texts. This study introduces a novel AI text classifier designed specifically for Arabic, tackling the distinct challenges inherent in processing this language. A parti...
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Chenhao Wu, Longgang Xiang, Libiao Chen, Qingcen Zhong and Xiongwei Wu
With the development of location-based services and data collection equipment, the volume of trajectory data has been growing at a phenomenal rate. Raw trajectory data come in the form of sequences of ?coordinate-time-attribute? triplets, which require c...
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Weiying Wang and Toshihiro Osaragi
The generation and prediction of daily human mobility patterns have raised significant interest in many scientific disciplines. Using various data sources, previous studies have examined several deep learning frameworks, such as the RNN and GAN, to synth...
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Benjamin Burrichter, Juliana Koltermann da Silva, Andre Niemann and Markus Quirmbach
This study employs a temporal fusion transformer (TFT) for predicting overflow from sewer manholes during heavy rainfall events. The TFT utilised is capable of forecasting overflow hydrographs at the manhole level and was tested on a sewer network with 9...
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Lexin Zhang, Kuiheng Chen, Liping Zheng, Xuwei Liao, Feiyu Lu, Yilun Li, Yuzhuo Cui, Yaze Wu, Yihong Song and Shuo Yan
This study introduces a novel high-accuracy fruit fly detection model based on the Transformer structure, specifically aimed at addressing the unique challenges in fruit fly detection such as identification of small targets and accurate localization agai...
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