Sequence Recommendation Method Based on RoBERTa and Graph-Enhanced Transformer [PDF]
Since the emergence of recommendation systems, further development of recommendation algorithms has been constrained by limited data. To reduce the impact of data sparsity and enhance the utilization of nonrated data, text-recommendation models based on ...
WANG Minghu, SHI Zhikui, SU Jia, ZHANG Xinsheng
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[Electrocardiogram signal classification based on fusion method of residual network and self-attention mechanism]. [PDF]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi, 2023 Yuan C, Liu Z, Wang C, Yang F.
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Text Classification Method Based on Contrastive Learning and Attention Mechanism [PDF]
Text classification is a basic task in the field of natural language processing and plays an important role in information retrieval, machine translation, sentiment analysis, and other applications.
Lai QIAN, Weiwei ZHAO
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[Whole-brain parcellation for macaque brain magnetic resonance images based on attention mechanism and multi-modality feature fusion]. [PDF]
Nan Fang Yi Ke Da Xue Xue Bao, 2023 Wu X, Zhang Y, Zhang H, Zhong T.
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Efficient End-to-End Spacecraft Component Detection Based on Residual Self-attention and Separated Set Matching [PDF]
The rapid development of space technology in China has led to a multitude of spacecraft launches. However, these spacecraft are expected to experience the influence of uncontrollable factors such as radiation and temperature changes during operation ...
Ming CHEN, Yanfei NIU, Li DUAN, Tieliang GAO, Yangyang CHU, Jie CAO
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智能科学与技术学报针对数字货币量化交易中存在的问题，即大量且复杂因子以及因子状态空间维度较高，导致交易模型制定策略的准确性和风险控制能力难以兼顾，提出了一种改进的OAC模型——OAC_LSTM_ATT。该模型采用了LSTM和多头注意力机制来优化OAC的网络结构，从而提高OAC对时间序列数据的建模能力和泛化能力。通过这种融合，智能体在量化交易环境中可以更加灵活和准确地做出交易决策，进一步提高交易策略的质量和效果。实验结果显示，在比特币市场中，累计收益率达到了16.36%，最大回撤率为9.08%，夏普比为0.014 ...
许波, 贺一峻, 李祥霞
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[Medical nucleus image segmentation network based on convolution and attention mechanism]. [PDF]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi, 2022 Zhi P, Deng J, Zhong Z.
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Gaoya dianqi基于无人机航拍的电力巡检成为目前绝缘子缺陷检测方法的主流，但当遇到图像特征不够明显或干扰特征较多等问题时，绝缘子缺陷识别困难，检测精度不高。由此，提出了一种基于改进YOLOv5s的绝缘子缺陷检测方法。首先，重新设计卷积模块，然后将CA注意力机制与其相融合，并且在主干网络加入注意力机制与颈部网络的特征图进行多尺度特征融合，抑制复杂环境下的干扰特征，专注缺陷特征提取；其次，对空间金字塔池化结构（SPPF）进行改进，扩大感受野，减少被模型过滤掉的有用信息；接着，将Transformer与C3模块中的残差结构 ...
彭晏飞, 袁晓龙, 赵涛, 陈炎康
doaj
[Prediction of microvascular invasion in hepatocellular carcinoma with magnetic resonance imaging using models combining deep attention mechanism with clinical features]. [PDF]
Nan Fang Yi Ke Da Xue Xue Bao, 2023 Gong G +6 more
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Dianxin kexue现有基于深度学习的调制识别在训练阶段需要大量IQ信号样本，而复杂电磁环境中很难获取大量样本，导致基于深度学习的调制识别算法泛化性能下降。针对网络泛化能力差的问题，提出了一种基于信号增强的调制识别（signal enhancement based modulation recognition，SEBMR）算法。首先，设计了捕获IQ信号全局特征的特征提取及重构模块；其次，提出了基于辅助分类生成对抗网络（auxiliary classifier generative adversarial network ...
程风云, 周金
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