Landing page component classification with convolutional neural networks for online advertising

机译：登陆页面组件与卷积神经网络进行在线广告

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Pages on digital platforms used for online advertising in order to attract customer attention for a target product are called landing pages. The aim of landing pages is to increase advertisement conversion rates using metrics like clicks, views or subscriptions. In this study, a method is presented to automatically detect the most commonly used components on landing pages; buttons, texts and checkboxes. Landing page images given as inputs, are segmented by morphological and thresholding-based image analysis methods, and each segment is classified using Convolutional Neural Networks (CNN). The proposed method is anticipated to be an important step in the process of automatically designing landing pages with high advertisement conversion rates by segmenting pages into components that have higher performance metrics. In preliminary experiments, high accuracy is achieved in the test data set.

机译：用于在线广告的数字平台上的页面，以吸引目标产品的客户注意称为着陆页。登陆页面的目的是使用像点击，视图或订阅等度量来增加广告转换率。在本研究中，提出了一种方法，以自动检测着陆页面上最常用的组件;按钮，文本和复选框。作为输入给出的降落页面图像被形态学和基于阈值的图像分析方法分段，并且每个段使用卷积神经网络（CNN）进行分类。预计所提出的方法是通过将页面分段为具有更高性能度量的组件自动设计具有高广告转换率的降落页面的过程中的一个重要步骤。在初步实验中，在测试数据集中实现了高精度。

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《Signal Processing and Communications Applications Conference》|2018年|672p|共4页
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作者
Gül?ah Ayhan; ?a?la ?enel; Zeynep Eda Uran; Beh?et Ugur T?reyin;
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中图分类 TN911.7-53;
关键词
Dogs; Image segmentation; Convolutional neural networks; Pattern recognition; Advertising; Measurement; Image analysis;

机译：狗;图像分割;卷积神经网络;模式识别;广告;测量;图像分析;

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4. Landing page component classification with convolutional neural networks for online advertising [C] . Gülşah Ayhan, Çağla Şenel, Zeynep Eda Uran, Signal Processing and Communications Applications Conference . 2018

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Landing page component classification with convolutional neural networks for online advertising

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