Results 81 to 90 of about 844 (118)
Unsupervised intrusion detection model based on temporal convolutional network [PDF]
Most existing intrusion detection models rely on long short-term memory (LSTM) networks to consider time-dependencies among data. However, LSTM’s sequential data processing significantly increases computational complexity and memory consumption during ...
DING Jiawei, FENG Guanghui, LIAO Jinju
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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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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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Survey on Visual Transformer for Image Classification [PDF]
Transformer is a deep learning model based on the self-attention mechanism, showing tremendous potential in computer vision. In image classification tasks, the key challenge lies in efficiently and accurately capturing both local and global features of ...
PENG Bin, BAI Jing, LI Wenjing, ZHENG Hu, MA Xiangyu
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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
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Zhongguo shiyan zhenduanxue, 2022 目的 通过免疫方法制备视神经炎动物模型，并探讨其潜在发病机制。方法 通过侧脑室注射人体补体（hc）及水通道蛋白4抗体（aquaporin 4antibody,AQP4-Ab）的方法共同免疫C57BL/6小鼠，并通过IL-17腹腔注射方法以强化小鼠体内的免疫反应，获得自身免疫性视神经炎鼠模型，通过行为学表现进行鉴定是否存在相似的临床特点，采用闪光诱发电位（F-VEP）方法检测是否存在视神经脱髓鞘情况。结果 行为学上的观察发现自身免疫性视神经炎模型鼠出现视力障碍、失明等表现，模型组较对照组分别在35d ...
郭洪亮, 沈笑然
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Fault diagnosis of piston pump based on global attention residual shrinkage network [PDF]
ObjectiveAiming at the problem of insufficient feature extraction in traditional neural networks under strong noise interference, a new global attention residual shrinkage network is proposed for accurate diagnosis of piston pump faults in complex ...
Guanhui ZHAO, Jun WU, Ke WU, Xiaoqi WANG
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Vehicle trajectory prediction based on spatio-temporal Transformer feature fusion [PDF]
In complex traffic environments, autonomous vehicles must thoroughly analyze the motion direction, speed, and other information of surrounding traffic objects to accurately predict future trajectories. A network model based on spatio-temporal Transformer
WAN Zilu, WANG Wei, ZHAO Wenhong
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Huli yanjiu, 2008 摘要： （免费在线浏览）随着人们健康需求的日益增长和医疗体制改革的不断深化，医疗服务行业正面临着新的机遇与挑战，只有不断强化公共卫生意识，不断壮大公共卫生应急体系，不断加固疾病防控防线，才能从容不迫地应对各种公共卫生危机。而在“非典”巨大震撼之后应用而生的公共卫生体系的主力军新建传染病医院的建设与发展已成为人们关注的重点。
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Research Review of Deep Learning in Colon Polyp Image Segmentation [PDF]
Colorectal polyp is an abnormal tissue growing in the gastrointestinal tract with the potential to develop into colorectal cancer. Therefore, early detection and removal of colorectal polyps are crucial for preventing colorectal cancer.
LI Guowei, LIU Jing, CAO Hui, JIANG Liang
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