由于多模态遥感图像在光谱成份上存在巨大的差异,传统图像配准算法在该类图像的配准中正确率非常低。针对这一难题,提出了一种利用风格迁移和特征点的图像配准算法。首先,利用卷积神经网络对基准图像的风格特征以及待配准图像的内容特征进行抽取并重新组合,得到一幅与基准图像差异性较小的生成图像;其次,通过图像分割的方法分离出待配准图像中没有明显纹理信息的部分,清除生成图像中多余的纹理;最后,使用加速鲁棒性特征(speed up robust features,SURF)算法提取特征点,进行图像配准。实验结果表明,与传统图像配准算法相比,该方法有效提高了多模态遥感图像配准的正确率和鲁棒性。
文章深入探讨了基于OBE的《操作系统》课程多途径混合式的教学方法与实践。这种混合学习模式整合了课堂教学、网络学习与交互以及实验实训等多途径学习形态,旨在提升学生的创新与实践能力。文章首先分析了基于OBE构建混合学习模式的指导思想,然后从教材建设、课堂闭环、实践重构、学情考核四个方面详细阐述了多途径混合学习模式的构建和具体实施方案,最后总结了实施效果。This paper discussed the multi-way blended teaching model and practice of the “Operating System” course based on OBE. This blended learning mode integrates multiple learning forms such as traditional classroom teaching, online learning and interaction, and experimental training, with the goal to enhance students’ innovation and practical abilities. The paper begins by analyzing the guiding ideology of constructing a blended learning mode based on OBE, then elaborates on the construction and implementation process from four aspects in detail, and finally summarizes the implementation effect.
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