Logo Detection Using Machine Learning Algorithm : A Survey

Jay Sanghvi, Jay Rathod, Sakshi Nemade, Hasti Panchal, A. Pavate
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引用次数: 1

Abstract

As more and more logos are produced, logo detection has gradually grown in popularity as study across numerous jobs and sectors. Deep learning-based solutions, which make use of numerous data sets,learning techniques, network designs, etc., have dominated recent advancements in this field. This research examines the progress made in the field of logo detection using deep learning approaches. In order to evaluate the efficacy of logo detection algorithms, which tend to be more diversified, difficult, and realistically reflective of real life, we first discuss a thorough background of the topic. The pros and disadvantages of each learning approach are then thoroughly analysed, along with the current logo detection strategies.To wrap up this study, we examine probable obstacles and provide the future directions for logo detecting development.
使用机器学习算法的标志检测:综述
随着越来越多的标志被生产出来,标志检测作为一项研究在许多工作和部门中逐渐流行起来。基于深度学习的解决方案利用了大量的数据集、学习技术、网络设计等,主导了该领域的最新进展。本研究考察了使用深度学习方法在标识检测领域取得的进展。为了评估标识检测算法的有效性,这些算法往往更多样化、更困难、更真实地反映现实生活,我们首先讨论了这个主题的全面背景。然后深入分析了每种学习方法的优缺点,以及当前的标识检测策略。为了总结这项研究,我们研究了可能的障碍,并为标志检测的发展提供了未来的方向。
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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