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Hyeon-Kyu Noh and Hong-June Park
A convolutional neural network (CNN) transducer decoder was proposed to reduce the decoding time of an end-to-end automatic speech recognition (ASR) system while maintaining accuracy. The CNN of 177 k parameters and a kernel size of 6 generates the proba...
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Gulshan Saleem, Usama Ijaz Bajwa, Rana Hammad Raza and Fan Zhang
Surveillance video analytics encounters unprecedented challenges in 5G and IoT environments, including complex intra-class variations, short-term and long-term temporal dynamics, and variable video quality. This study introduces Edge-Enhanced TempoFuseNe...
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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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Hui Sheng, Min Liu, Jiyong Hu, Ping Li, Yali Peng and Yugen Yi
Time-series data is an appealing study topic in data mining and has a broad range of applications. Many approaches have been employed to handle time series classification (TSC) challenges with promising results, among which deep neural network methods ha...
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Jing Yang, Hongyu Yang, Zhengyuan Wu and Xiping Wu
Due to increased air traffic flow, air traffic controllers (ATCs) operate in a state of high load or even overload for long periods of time, which can seriously affect the reliability and efficiency of controllers? commands. Thus, the early identificatio...
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Soumyashree Kar, Jason R. McKenna, Glenn Anglada, Vishwamithra Sunkara, Robert Coniglione, Steve Stanic and Landry Bernard
While study of ocean dynamics usually involves modeling deep ocean variables, monitoring and accurate forecasting of nearshore environments is also critical. However, sensor observations often contain artifacts like long stretches of missing data and noi...
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Ogbaje Andrew, Armando Apan, Dev Raj Paudyal and Kithsiri Perera
The accuracy of most SAR-based flood classification and segmentation derived from semi-automated algorithms is often limited due to complicated radar backscatter. However, deep learning techniques, now widely applied in image classifications, have demons...
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Songnan Chen, Mengxia Tang, Ruifang Dong and Jiangming Kan
The semantic segmentation of outdoor images is the cornerstone of scene understanding and plays a crucial role in the autonomous navigation of robots. Although RGB?D images can provide additional depth information for improving the performance of semanti...
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Yujia Zhang, Luteng Zhong, Yu Ding, Hongfeng Yu and Zhaoyu Zhai
Rice is a staple food for over half of the global population, but it faces significant yield losses: up to 52% due to leaf blast disease and brown spot diseases, respectively. This study aimed at proposing a hybrid architecture, namely ResViT-Rice, by ta...
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Niousha Ghannad and Kalpdrum Passi
Currently, video and digital images possess extensive utility, ranging from recreational and social media purposes to verification, military operations, legal proceedings, and penalization. The enhancement mechanisms of this medium have undergone signifi...
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