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Alvaro A. Teran-Quezada, Victor Lopez-Cabrera, Jose Carlos Rangel and Javier E. Sanchez-Galan
Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long?short-term memory (LSTM) have become a means for providing solutions to problem...
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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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Christopher Jun Qian Teh, Micheal Drieberg, Khairul Nisak Md Hasan, Abdul Latif Shah and Rizwan Ahmad
The use of photovoltaic (PV) panels in interior spaces is expected to increase due to the proliferation of low-power sensor devices in the IoT domain. PV models are critical for estimating the I?V curves that define their performance at various light int...
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Gustavo Rocha, Luís Mateus and Victor Ferreira
Building Information Modeling (BIM) has emerged as a revolutionary tool in the domain of architectural conservation and documentation. When combined with terrestrial 3D laser scanning, it presents a powerful method to capture and represent the intricate ...
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Xin Tian and Yuan Meng
Multi-relational graph neural networks (GNNs) have found widespread application in tasks involving enhancing knowledge representation and knowledge graph (KG) reasoning. However, existing multi-relational GNNs still face limitations in modeling the excha...
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Kara Combs, Adam Moyer and Trevor J. Bihl
Recently, generative artificial intelligence (GAI) has impressed the world with its ability to create text, images, and videos. However, there are still areas in which GAI produces undesirable or unintended results due to being ?uncertain?. Before wider ...
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Jungha Son and Boyoung Kim
The rapid global expansion of ChatGPT, which plays a crucial role in interactive knowledge sharing and translation, underscores the importance of comparative performance assessments in artificial intelligence (AI) technology. This study concentrated on t...
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Zepeng Wang, Yuan Chen and Juwei Zhang
In practical applications, the accuracy of domain terminology translation is an important criterion for the performance evaluation of domain machine translation models. Aiming at the problem of phrase mismatch and improper translation caused by word-by-w...
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Jian Xu, Xiaowen Zhou, Chaolin Han, Bing Dong and Hongwei Li
Accurate translation of aerial imagery to maps is a direction of great value and challenge in mapping, a method of generating maps that does not require using vector data as traditional mapping methods do. The tremendous progress made in recent years in ...
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Atnafu Lambebo Tonja, Olga Kolesnikova, Alexander Gelbukh and Grigori Sidorov
Despite the many proposals to solve the neural machine translation (NMT) problem of low-resource languages, it continues to be difficult. The issue becomes even more complicated when few resources cover only a single domain. In this paper, we discuss the...
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