基于人工智能平台的视频样本采集与处理方法研究

An Hu , Qi Wang , Xiaoguang Xu , Yao Zhao , Qian Ji , Lei Pei
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引用次数: 0

摘要

本文总结了基于人工智能平台的视频样本采集与处理方法,重点介绍了视频噪声消除、内容分割与分类、特征提取与表示技术。本文认为,深度学习技术,尤其是卷积神经网络,在图像识别和视频分析中展现出巨大潜力,有效提高了视频处理的自动化水平和准确性。本文探讨了建立大规模、高质量视频样本库的重要性,以及如何通过智能技术提高视频数据的处理效率和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Video Sample Collection and Processing Methods Based on Artificial Intelligence Platform
This paper summarizes the video sample collection and processing methods based on artificial intelligence platform, focusing on video noise cancellation, content segmentation and classification, and feature extraction and representation techniques. The paper believes that the deep learning technology, especially the convolutional neural network, shows great potential in image recognition and video analysis, and effectively improves the level of automation and accuracy of video processing. This paper discusses the importance of building a large-scale and high-quality video sample library, and how to improve the processing efficiency and accuracy of video data through intelligent technology.
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