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您的检索式：作者名="Baiying Lei"
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| 1 | Deep Learning in Medical Ultrasound Analysis: A Review显示文摘Ultrasound (US) has become one of the most commonly performed imaging modalities in clinical practice. It is a rapidly evolving technology with certain advantages and with unique challenges that include low imaging quality and high variability. From the perspective of image analysis, it is essential to develop advanced automatic US image analysis methods to assist in US diagnosis and/or to make such assessment more objective and accurate. Deep learning has recently emerged as the leading machine learning tool in various research fields, and especially in general imaging analysis and computer vision. Deep learning also shows huge potential for various automatic US image analysis tasks. This review first briefly introduces several popular deep learning architectures, and then summarizes and thoroughly discusses their applications in various specific tasks in US image analysis, such as classification, detection, and segmentation. Finally, the open challenges and potential trends of the future application of deep learning in medical US image analysis are discussed. | Shengfeng Liu Yi Wang Xin Yang Baiying Lei Li Liu Shawn Xiang Li Dong Ni Tianfu Wang | 2019 | Engineering2019，5，2： | 24 |
| 2 | 有同步和加密的一个多种用途的听觉的 watermarking 算法显示文摘我们建议二互补水位标在被使用的一个新多种用途的听觉的 watermarking 计划。为听觉的版权保护,有版权信息或签名的水位标数据被阿诺德转变首先加密。然后,水位标数据在低频率被插入获得坚韧性性能的最大的重要分离余弦变换(DCT ) 系数。为听觉的认证,一个混乱信号在高频率被插入检测捣弄的区域的不足道的 DCT 系数。而且,同步代码在听觉的统计特征被嵌入抵抗 desynchronization 攻击。试验性的结果证明我们的建议方法不能仅仅获得令人满意的察觉并且捣弄地点,而且完成无法感知和坚韧性到普通信号处理攻击,变,例如收割,并且时间规模修正(TSM ) 。比较结果证明我们的方法超过一些存在方法。 | Baiying LEI Ing Yann SOON | 2012 | Journal of Zhejiang University-Science C(Computers and Electronics)2012，13，1： | 1 |
| 3 | Blind and robust audio watermarking scheme based on SVD-DCT显示文摘 | LEI Baiying SOON I Y LI Zhen | 2011 | Signal Processing2011，91，8： | 1 |
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