Flowers Images Classification with Deep Learning: A Review

Q4 Mathematics
Asia Kamal Mustfa, S. Abdulateef, Qabas A. Hameed
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引用次数: 0

Abstract

Significant progress has been made in the field of digital image processing in recent years through the utilization of machine learning and deep learning, surpassing previous methods by a large margin. Deep learning methods allow devices such as computers and mobile to automatically understand pattern characteristics. This review paper highlights challenges and issues in machine-deep learning applied to the domain of flower classification. in addition, the datasets were extracted that were found in the literature. The review offered in this article can encourage researchers in the domain of agriculture inspired techniques research society to further enhance the efficacy of the AI methods and to use the different AI techniques in other fields for solving complicated real-life challenges. In addition, the article provides an overview of the artificial intelligence techniques employed in the field of flower recognition, detection, segmentation, and other applications, delivering the most delinquent and recent literature for solving issues for researchers in the area of flowers.
利用深度学习进行花卉图像分类:综述
近年来,通过利用机器学习和深度学习,数字图像处理领域取得了重大进展,大大超越了以往的方法。深度学习方法使计算机和移动设备等设备能够自动理解模式特征。本文重点介绍了机器深度学习应用于花卉分类领域所面临的挑战和问题,并提取了文献中的数据集。本文提供的综述可以鼓励农业启发技术研究会领域的研究人员进一步提高人工智能方法的功效,并在其他领域使用不同的人工智能技术来解决复杂的现实挑战。此外,文章还概述了人工智能技术在花卉识别、检测、分割等领域的应用,为花卉领域的研究人员提供了解决问题的最新文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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