Wireless sensornetworks (WSNs) have garnered significant attention for their ability to collect and transmit data in various applications. However, ensuring secure communication in WSNs poses significant challenges d...
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these underwater Acoustic sensornetworks (UWSNs) present unique challenges due to the harsh and dynamic underwater environment, making efficient communication protocols essential for their operation. this paper intro...
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To address the issue of insufficient military equipment sample data, which cannot meet the training requirements of deep neural networks and tends to cause overfitting, this paper introduces transfer learning technolo...
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this paper presents an innovative approach to image generation and audio playback through the fusion of deep convolutional neural networks (CNNs) and natural language processing. We propose a system that generates tex...
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this paper addresses the challenges in distributed simulation modeling of large-scale networks (LSIM - consist of hundreds of thousands of nodes). the focus is on the efficient mapping of LSIM onto a distributed simul...
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Chinese text error correction is to automatically detect errors or inappropriate expressions in a given Chinese text and output correct correction results according to the context and application scenarios. Existing r...
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ISBN:
(纸本)9798400716751
Chinese text error correction is to automatically detect errors or inappropriate expressions in a given Chinese text and output correct correction results according to the context and application scenarios. Existing research ideas mainly focus on two categories: rule-based and depth model-based, where depth model-based methods mainly focus on solving alignment-based errors and perform poorly on non-alignment-based errors. And withthe scarcity of manually labeled data, few works have considered using self-supervised training methods to pre-train the models. therefore, for the common multiple and omitted word errors in electric power article writing, this paper proposes a generative model-based error correction method for Chinese text. A large-scale error correction dataset is first constructed using a rule-based self-supervised approach and pretrained using a generalized domain dataset. then, in the incremental training phase, lexically supervised signals are added inside the model to enhance the model's error detection effect by means of lexical combination. Finally, the model is fine-tuned using a domain-specific self-supervised dataset. the effectiveness of the method in this paper is demonstrated by analyzing the experimental results in comparison with other models.
this study aims to recognise accelerometer-based human activities using ANN models. We used the UCI-HAR dataset, which is a widely used publicly available dataset containing accelerometer data for six daily activities...
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In this paper, we have designed a more efficient visual transformer G-SwinJSCC, for semantic image transmission. Compared to most methods that rely solely on Convolutional Neural networks (CNN), we utilize a combinati...
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Primarily employed to achieve this objective, wireless sensornetworks (WSNs) are designed to track environmental or physical conditions. they obtain data from their environment efficiently and deliver it all at once ...
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this paper explores the applications and challenges of graph neural networks (GNNs) in processing complex graph data brought about by the rapid development of the Internet. Given the heterogeneity and redundancy probl...
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