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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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Nguyen Trung Tuan, Philip Moore, Dat Ha Vu Thanh and Hai Van Pham
ChatGPT plays significant roles in the third decade of the 21st Century. Smart cities applications can be integrated with ChatGPT in various fields. This research proposes an approach for developing large language models using generative artificial intel...
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Milo? Bogdanovic, Jelena Kocic and Leonid Stoimenov
Language is a unique ability of human beings. Although relatively simple for humans, the ability to understand human language is a highly complex task for machines. For a machine to learn a particular language, it must understand not only the words and r...
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Somayeh Shahrabadi, Telmo Adão, Emanuel Peres, Raul Morais, Luís G. Magalhães and Victor Alves
The proliferation of classification-capable artificial intelligence (AI) across a wide range of domains (e.g., agriculture, construction, etc.) has been allowed to optimize and complement several tasks, typically operationalized by humans. The computatio...
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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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Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an...
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Thomas Kopalidis, Vassilios Solachidis, Nicholas Vretos and Petros Daras
Recent technological developments have enabled computers to identify and categorize facial expressions to determine a person?s emotional state in an image or a video. This process, called ?Facial Expression Recognition (FER)?, has become one of the most ...
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Ying-Hsun Lai, Shin-Yeh Chen, Wen-Chi Chou, Hua-Yang Hsu and Han-Chieh Chao
Federated learning trains a neural network model using the client?s data to maintain the benefits of centralized model training while maintaining their privacy. However, if the client data are not independently and identically distributed (non-IID) becau...
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Reenu Mohandas, Mark Southern, Eoin O?Connell and Martin Hayes
Deep learning based visual cognition has greatly improved the accuracy of defect detection, reducing processing times and increasing product throughput across a variety of manufacturing use cases. There is however a continuing need for rigorous procedure...
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Zifeng Zhao, Xuesong Yang, Ding Ding, Qiangyong Wang, Feiran Zhang, Zhicheng Hu, Kaikai Xu and Xuelin Wang
Physics-informed DeepONet (PI_DeepONet) is utilized for the reconstruction task of structural displacement based on measured strain. For beam and plate structures, the PI_DeepONet is built by regularizing the strain?displacement relation and boundary con...
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