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Xiaobo Zhang, Huashun Li, Jingzhao Li and Xuehai Zhou
The rapid and accurate detection of orthopedic medical devices is pivotal in enhancing health care delivery, particularly by improving workflow efficiency. Despite advancements in medical imaging technology, current detection models often fail to meet th...
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Ting Guo, Nurmemet Yolwas and Wushour Slamu
Recently, the performance of end-to-end speech recognition has been further improved based on the proposed Conformer framework, which has also been widely used in the field of speech recognition. However, the Conformer model is mostly applied to very wid...
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Xin Wang, Yi Li, Yaxi Xu, Xiaodong Liu, Tao Zheng and Bo Zheng
Data-driven Remaining Useful Life (RUL) prediction is one of the core technologies of Prognostics and Health Management (PHM). Committed to improving the accuracy of RUL prediction for aero-engines, this paper proposes a model that is entirely based on t...
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Fan Liu and Jiandong Fang
Classroom interactivity is one of the important metrics for assessing classrooms, and identifying classroom interactivity through classroom image data is limited by the interference of complex teaching scenarios. However, audio data within the classroom ...
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Shih-An Li, Yu-Ying Liu, Yun-Chien Chen, Hsuan-Ming Feng, Pi-Kang Shen and Yu-Che Wu
This paper designed a voice interactive robot system that can conveniently execute assigned service tasks in real-life scenarios. It is equipped without a microphone where users can control the robot with spoken commands; the voice commands are then reco...
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Yiming Hu, Bin Wen, Yongsheng Ye and Chao Yang
Insulators find extensive use across diverse facets of power systems, playing a pivotal role in ensuring the security and stability of electrical transmission. Detecting insulators is a fundamental measure to secure the safety and stability of power tran...
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Zhangfang Hu, Libujie Chen, Yuan Luo and Jingfan Zhou
The proposed method in this study can be used in EEG emotion recognition and achieve better results.
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Roberto Pecoraro, Valerio Basile and Viviana Bono
Since the Transformer architecture was introduced in 2017, there has been many attempts to bring the self-attention paradigm in the field of computer vision. In this paper, we propose LHC: Local multi-Head Channel self-attention, a novel self-attention m...
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Shangyi Yan, Jingya Wang and Zhiqiang Song
To address the shortcomings of existing deep learning models and the characteristics of microblog speech, we propose the DCCMM model to improve the effectiveness of microblog sentiment analysis. The model employs WOBERT Plus and ALBERT to dynamically enc...
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Fei Xie, Dalong Zhang and Chengming Liu
Transformer models are now widely used for speech processing tasks due to their powerful sequence modeling capabilities. Previous work determined an efficient way to model speaker embeddings using the Transformer model by combining transformers with conv...
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