DeepCap:一种用于描述黑白图像的深度学习模型

Vaibhav Pandit, Rishabh Gulati, Chaitanya Singla, Sandeep Kr. Singh
{"title":"DeepCap:一种用于描述黑白图像的深度学习模型","authors":"Vaibhav Pandit, Rishabh Gulati, Chaitanya Singla, Sandeep Kr. Singh","doi":"10.1109/Confluence47617.2020.9058164","DOIUrl":null,"url":null,"abstract":"Captioning of colored images has been around for quite some time now, it uses object detection and the spatial relation between the objects to generate captions. There have been numerous approaches to caption colorized images in the past, but there have been a very few. In this paper we present an approach to caption Black and white images without any attempt of colorization. We have used transfer learning to implement Inception V3, a CNN model developed by Google and a runner up in the ImageNet image classification challenge, to generate captions from Black and white images achieving an accuracy of 45.77% on the validation set.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"DeepCap: A Deep Learning Model to Caption Black and White Images\",\"authors\":\"Vaibhav Pandit, Rishabh Gulati, Chaitanya Singla, Sandeep Kr. Singh\",\"doi\":\"10.1109/Confluence47617.2020.9058164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Captioning of colored images has been around for quite some time now, it uses object detection and the spatial relation between the objects to generate captions. There have been numerous approaches to caption colorized images in the past, but there have been a very few. In this paper we present an approach to caption Black and white images without any attempt of colorization. We have used transfer learning to implement Inception V3, a CNN model developed by Google and a runner up in the ImageNet image classification challenge, to generate captions from Black and white images achieving an accuracy of 45.77% on the validation set.\",\"PeriodicalId\":180005,\"journal\":{\"name\":\"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Confluence47617.2020.9058164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Confluence47617.2020.9058164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

彩色图像的字幕已经存在很长一段时间了,它使用对象检测和对象之间的空间关系来生成字幕。在过去,有许多方法可以为彩色图像添加标题,但很少。在本文中,我们提出了一种方法来说明黑白图像没有任何尝试着色。我们使用迁移学习来实现Inception V3,这是一个由Google开发的CNN模型,也是ImageNet图像分类挑战的亚军,它从黑白图像中生成字幕,在验证集上实现了45.77%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
DeepCap: A Deep Learning Model to Caption Black and White Images
Captioning of colored images has been around for quite some time now, it uses object detection and the spatial relation between the objects to generate captions. There have been numerous approaches to caption colorized images in the past, but there have been a very few. In this paper we present an approach to caption Black and white images without any attempt of colorization. We have used transfer learning to implement Inception V3, a CNN model developed by Google and a runner up in the ImageNet image classification challenge, to generate captions from Black and white images achieving an accuracy of 45.77% on the validation set.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Identification of the most efficient algorithm to find Hamiltonian Path in practical conditions Segmentation and Detection of Road Region in Aerial Images using Hybrid CNN-Random Field Algorithm A Novel Approach for Isolation of Sinkhole Attack in Wireless Sensor Networks Performance Analysis of various Information Platforms for recognizing the quality of Indian Roads Time Series Data Analysis And Prediction Of CO2 Emissions
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1