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浏览/检索结果: 共7条，第1-7条 帮助 限定条件 专题：北京航空航天大学    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Adapting Word Embeddings to Traceability Recovery 会议论文 Proceedings of 2018 International Conference on Information Systems and Computer Aided Education, ICISCAE 2018, 2018-07-06 作者:  Tian, Q.;  Cao, Q.;  Sun, Q. 收藏  |  浏览/下载：10/0  |  提交时间：2019/12/30 Embeddings  Information retrieval  Information systems  Information use  Learning systems  Semantics  Vector spaces  Contrast experiment  Embedding technique  Machine learning methods  Out of vocabulary words  similarity  traceability  Traceability links  Vector space models  Computer aided instruction   3D printing fault detection based on process data 期刊论文 Lecture Notes in Electrical Engineering, 2019, 卷号: 529, 页码: 385-396 作者:  Li, B.;  Zhang, L.;  Ren, L.;  Luo, X. 收藏  |  浏览/下载：9/0  |  提交时间：2019/12/30 Fault detection  Learning systems  Printing presses  3D printing process  Classification models  Fault prediction  Logistic regressions  Machine learning methods  Multiple parameters  Rapid prototyping technology  Real-time detection  3D printers   A Novel Intrusion Detection System Based on Advanced Naive Bayesian Classification 期刊论文 Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2018, 卷号: 211, 页码: 581-588 作者:  Wang, Y.;  Li, Y.;  Tian, D.;  Wang, C.;  Wang, W. 收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30 5G mobile communication systems  Classification (of information)  Computer crime  Learning systems  Mercury (metal)  Network security  Pattern recognition  Pattern recognition systems  Security of data  Wireless networks  Classification results  Detection performance  Intrusion Detection Systems  Machine learning models  Naive Bayesian classification  ReliefF  Relieff algorithms  True positive rates  Intrusion detection   A supervised abundance estimation method for hyperspectral unmixing 期刊论文 REMOTE SENSING LETTERS, 2018, 卷号: 9, 页码: 383-392 作者:  Xu, Xia;  Shi, Zhenwei;  Pan, Bin 收藏  |  浏览/下载：12/0  |  提交时间：2019/12/30 Deep learning  Image processing  Independent component analysis  Learning systems  Mapping  Mixing  Mixtures  Spectroscopy  Supervised learning  Abundance estimation  Hyperspectral unmixing  Microscopic interaction  Non-linear mixture models  Non-linear unmixing  Nonlinear mixing models  Supervised machine learning  Synthetic and real data  Nonlinear analysis  data set  estimation method  image analysis  numerical method  numerical model  pixel  supervised learning   A novel method of overrun risk measurement and assessment using large scale QAR Data 会议论文 Proceedings - IEEE 4th International Conference on Big Data Computing Service and Applications, BigDataService 2018, 2018-03-26 作者:  Lv, H.;  Yu, J.;  Zhu, T. 收藏  |  浏览/下载：12/0  |  提交时间：2019/12/30 Aircraft accidents  Decision trees  Learning systems  Risk assessment  Supersonic aerodynamics  Commercial aircraft  Feature dimensions  Flight parameters  Machine learning models  Overrun risk mea surement  QAR Data  Random forests  Risk measurement  Big data   An asymmetrical acoustic field detection system for daily tooth brushing monitoring 会议论文 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings 作者:  Ouyang, Z.;  Hu, J.;  Niu, J.;  Qi, Z. 收藏  |  浏览/下载：12/0  |  提交时间：2019/12/30 Acoustic fields  Artificial intelligence  Bluetooth  Decision trees  Earphones  Hidden Markov models  Learning systems  Microphones  Mobile computing  Support vector machines  Acoustic features  Acoustic signals  Field detections  Machine learning models  Monitoring system  Throat microphones  Time and frequency domains  Tooth brushing  Pattern recognition   A two-layer structure prediction framework for microscopy cell detection 期刊论文 COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2015, 卷号: 41, 页码: 29-36 作者:  Xu Yan;  Wu Weiying;  Chang Eric I-Chao;  Chen Danny;  Mu Jian 收藏  |  浏览/下载：3/0  |  提交时间：2020/01/06 Microscopy cell detection  layered models  Structural prediction  Computer vision  Machine learning