mial
- 网络孟买国际机场私营有限公司
mial-
The function is proved to reach the same result with Mobius transformation as identifying the " optimal " parametrization of the same polyno - mial curve .
采用这种重新参数化方法求出的曲线最优参数化与采用Mobius变换求出的最优参数化是一样的。实例表明了该方法的有效性。
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For image-level retrieval based on regional information , we model the image structure with multiple-instance learning which belongs to structural learning framework , and introduce multiple instance active learning ( MIAL ) to reduce manual labeling and solve the problem of lacking labeled-samples .
对基于区域信息的图像层检索，采用多示例学习进行建模，并利用多示例主动学习以减少人工标注的工作量，解决标注样本缺乏问题。