基于深度学习的系统用房图像快速识别和分类算法
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Fast Recognition and Classification Algorithm For Housing Images Based on Deep Learning System
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    摘要:

    针对室内图像识别边界相似区域识别模糊导致识别精度较低的问题,为实现高精度识别,引入深度学习算法,对其图像构成像素关系进行全新设计。具体计算过程包括:基于深度学习的室内图像凹凸关系分析、图像深度学习融合识别、深度学习特征下室内图像分类编码计算3部分。通过上述过程实现图像的高精准识别与分类。实验数据对比结果表明:该算法具备较高的有效性,满足了应用性相关要求,符合算法推广相关标准。

    Abstract:

    In order to solve the problem of low recognition accuracy caused by fuzzy recognition of similar areas in indoor image recognition, a deep learning algorithm is introduced to achieve high-precision recognition, and a new design is made for the pixel relationship of the image. The specific calculation process includes three parts: concave-convex relationship analysis of indoor images based on deep learning, image fusion recognition based on deep learning, and indoor image classification and coding calculation based on deep learning features. Through the above process, the high-precision recognition and classification of images are realized. Experimental data comparison results show that the algorithm has high effectiveness, meets the requirements of application, and meets the standards of algorithm promotion.

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王海燕.基于深度学习的系统用房图像快速识别和分类算法[J].,2026,45(01).

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  • 收稿日期:2024-11-10
  • 最后修改日期:2024-12-11
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  • 在线发布日期: 2026-02-11
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