Predicting CTR of Regional Flyer Images Using CNN

Author:

Inoue Daichi1,Matsumoto Shimpei2

Affiliation:

1. Hiroshima Institute of Technology,Graduate School of Science and Technology,Hiroshima,Japan

2. Hiroshima Institute of Technology,Faculty of Applied Information Science,Hiroshima,Japan

Funder

Japan Society for the Promotion of Science

Publisher

IEEE

Reference4 articles.

1. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Int Conference on Machine Learning,2015

2. Deep Residual Learning for Image Recognition

3. Deep CTR Prediction in Facebook Ads;iwazaki,0

4. Everybody’s Town BBS:—Development and Operation of a Smartphone Application to Share the Information of Micro Community Activities——;matsumoto;The Transactions of the Institute of Electrical Engineers of Japan C A Publication of Electronics Information and Systems Society,2020

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Proposal of a CNN-based Method for Predicting the Number of Clicks on Micro-event Flyer Images;IEEJ Transactions on Electronics, Information and Systems;2024-09-01

2. Predicting the number of clicks on a local information sharing service using a CNN considering micro-event information;2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI);2023-07-08

3. Systematic Literature Review on Click Through Rate Prediction;New Trends in Database and Information Systems;2023

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