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Online Education Classroom Intelligent Management System Based on Tensor CS Reconstruction Model

机译:基于张量CS重构模型的在线教育教室智能管理系统

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摘要

To study a high-efficiency online classroom intelligent management system, this article builds an artificial intelligence classroom management system based on the tensor CS reconstruction model. Moreover, this study uses the cosine function to represent the data energy fitting of the traditional active contour model and proposes a local cosine fitting energy active contour model based on partial image restoration, which is used for image and composite image segmentation. Simultaneously, this study proposes a new type of super-resolution algorithm. This algorithm performs Fourier transform of a low-resolution image into a frequency range and then performs an inverse Fourier transform on the image expanded in the frequency range to obtain the initial high-resolution image and finally reconstructs a new super-resolution image using the frequency-domain compressed data of the high-resolution image. Finally, this study verifies and analyzes the performance of the model through experiments. The research results are basically consistent with the expectations of the model.
机译:为研究一种高效的在线教室智能管理系统,本文构建了一种基于张量CS重构模型的人工智能教室管理系统。此外,利用余弦函数表示传统主动等值线模型的数据能量拟合,提出一种基于局部图像恢复的局部余弦拟合能主动等值线模型,用于图像和复合图像分割。同时,提出了一种新型的超分辨率算法。该算法将低分辨率图像进行傅里叶变换到一个频率范围内,然后对在频率范围内扩展的图像进行逆傅里叶变换,得到初始的高分辨率图像,最后利用高分辨率图像的频域压缩数据重建新的超分辨率图像。最后,通过实验对模型的性能进行了验证和分析。研究结果与模型预期基本一致。

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