Multiple instance learning based deep CNN for image memorability prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
http://link.springer.com/content/pdf/10.1007/s11042-019-08202-y.pdf
Reference58 articles.
1. Anderson AK, Wais PE, Gabrieli JD (2006) Emotion enhances remembrance of neutral events past. Proc Natl Acad Sci 103(5):1599–1604
2. Baveye Y, Cohendet R, Perreira Da Silva M, Le Callet P (2016) Deep learning for image memorability prediction: the emotional bias. In: Proceedings of the 2016 ACM on multimedia conference. ACM, pp 491–495
3. Blackwell AF (1997) Correction: a picture is worth 84.1 words. In: Proceedings of the first ESP student workshop, pp 15–22
4. Borkin MA, Vo AA, Bylinskii Z, Isola P, Sunkavalli S, Oliva A, Pfister H (2013) What makes a visualization memorable? IEEE Trans Vis Comput Graph 19(12):2306–2315
5. Bradley MM, Greenwald MK, Petry MC, Lang PJ (1992) Remembering pictures: pleasure and arousal in memory. J Exp Psychol Learn Mem Cogn 18(2):379
Cited by 5 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. Comprehensive Literature Survey on Deep Learning Used in Image Memorability Prediction and Modification;International Conference on Innovative Computing and Communications;2023-10-26
2. Modular Memorability: Tiered Representations for Video Memorability Prediction;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06
3. A Survey on Image Memorability Prediction: From Traditional to Deep Learning Models;2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET);2022-03-03
4. A Cross-Modal Image and Text Retrieval Method Based on Efficient Feature Extraction and Interactive Learning CAE;Scientific Programming;2022-01-10
5. ResMem-Net: memory based deep CNN for image memorability estimation;PeerJ Computer Science;2021-11-05
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3