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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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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Bohdan Petryshyn, Serhii Postupaiev, Soufiane Ben Bari and Armantas Ostreika
The development of autonomous driving models through reinforcement learning has gained significant traction. However, developing obstacle avoidance systems remains a challenge. Specifically, optimising path completion times while navigating obstacles is ...
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Yongen Lin, Dagang Wang, Tao Jiang and Aiqing Kang
Reliable streamflow forecasting is a determining factor for water resource planning and flood control. To better understand the strengths and weaknesses of newly proposed methods in streamflow forecasting and facilitate comparisons of different research ...
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Hellena Hempe, Alexander Bigalke and Mattias Paul Heinrich
Background: Degenerative spinal pathologies are highly prevalent among the elderly population. Timely diagnosis of osteoporotic fractures and other degenerative deformities enables proactive measures to mitigate the risk of severe back pain and disabilit...
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Sofía Ramos-Pulido, Neil Hernández-Gress and Gabriela Torres-Delgado
Current research on the career satisfaction of graduates limits educational institutions in devising methods to attain high career satisfaction. Thus, this study aims to use data science models to understand and predict career satisfaction based on infor...
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Fenfang Li, Zhengzhang Zhao, Li Wang and Han Deng
Sentence Boundary Disambiguation (SBD) is crucial for building datasets for tasks such as machine translation, syntactic analysis, and semantic analysis. Currently, most automatic sentence segmentation in Tibetan adopts the methods of rule-based and stat...
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Yee Sye Lee, Ali Rashidi, Amin Talei and Daniel Kong
In recent years, mixed reality (MR) technology has gained popularity in construction management due to its real-time visualisation capability to facilitate on-site decision-making tasks. The semantic segmentation of building components provides an attrac...
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Weiwei Yuan, Wanxia Yang, Liang He, Tingwei Zhang, Yan Hao, Jing Lu and Wenbo Yan
The extraction of entities and relationships is a crucial task in the field of natural language processing (NLP). However, existing models for this task often rely heavily on a substantial amount of labeled data, which not only consumes time and labor bu...
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Sadia Alam Shammi, Yanbo Huang, Gary Feng, Haile Tewolde, Xin Zhang, Johnie Jenkins and Mark Shankle
The application of remote sensing, which is non-destructive and cost-efficient, has been widely used in crop monitoring and management. This study used a built-in multispectral imager on a small unmanned aerial vehicle (UAV) to capture multispectral imag...
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