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针对机器问答中多跳问题的深度学习网络模型 被引量:1
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作者 邵霭 许彩娥 +2 位作者 万健 张蕾 郑慧琳 《浙江科技学院学报》 CAS 2022年第5期419-425,共7页
多跳问答(multi-hop question answering,multi-hop QA)是文本问答的一项重要且具有挑战性的任务。针对现有方法在解决多跳问题时答案推理能力弱、答案寻找的准确率低等问题提出一种多跳问题的深度学习网络模型AGTNet(albert graph atte... 多跳问答(multi-hop question answering,multi-hop QA)是文本问答的一项重要且具有挑战性的任务。针对现有方法在解决多跳问题时答案推理能力弱、答案寻找的准确率低等问题提出一种多跳问题的深度学习网络模型AGTNet(albert graph attention network,轻量双向编码图注意力网络)。首先在神经网络隐藏层使用参数共享和矩阵分解技术,然后使用点积计算方式进行答案预测,最后使用已标注的数据集对AGTNet模型进行训练验证。试验结果表明,本模型经过训练后在测试集上的F_(1)值达到70.4;与现有的多跳问答推理模型相比,本模型拥有较优的实体级推理能力,能够有效提高多跳问答推理能力,从而提升了问答系统的响应速度和准确率。本研究结果为问答系统和多轮对话机器人的研发提供了理论依据。 展开更多
关键词 多跳问答 深度学习 表征提取 问答推理
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Fusion network for small target detection based on YOLO and attention mechanism
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作者 xu caie DONG Zhe +3 位作者 ZHONG Shengyun CHEN Yijiang PAN Sishun WU Mingyang 《Optoelectronics Letters》 EI 2024年第6期372-378,共7页
Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of r... Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of researches, such as small target detection in complex environments is susceptible to background interference and poor detection results. To solve these issues, this study proposes a method which introduces the attention mechanism into the you only look once(YOLO) network. In addition, the amateur-produced mask dataset was created and experiments were conducted. The results showed that the detection effect of the proposed mothed is much better. 展开更多
关键词 Fusion network for small target detection based on YOLO and attention mechanism
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