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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Suping Wang, Ligu Zhu, Lei Shi, Hao Mo and Songfu Tan
Cross-modal retrieval aims to elucidate information fusion, imitate human learning, and advance the field. Although previous reviews have primarily focused on binary and real-value coding methods, there is a scarcity of techniques grounded in deep repres...
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Wenxiao Li, Hongyan Mei, Yutian Li, Jiayao Yu, Xing Zhang, Xiaorong Xue and Jiahao Wang
Due to the fast retrieval speed and low storage cost, cross-modal hashing has become the primary method for cross-modal retrieval. Since the emergence of deep cross-modal hashing methods, cross-modal retrieval significantly improved. However, the existin...
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Rui Zhang, Chengrong Xue, Qingfu Qi, Liyuan Lin, Jing Zhang and Lun Zhang
The enrichment of social media expression makes multimodal sentiment analysis a research hotspot. However, modality heterogeneity brings great difficulties to effective cross-modal fusion, especially the modality alignment problem and the uncontrolled ve...
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Xin Tong, Bo Jin, Jingya Wang, Ying Yang, Qiwei Suo and Yong Wu
In recent years, the number of malicious web pages has increased dramatically, posing a great challenge to network security. While current machine learning-based detection methods have emerged as a promising alternative to traditional detection technique...
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Kangying Li, Jiayun Wang, Biligsaikhan Batjargal and Akira Maeda
In recent years, artworks have been increasingly digitized and built into databases, and such databases have become convenient tools for researchers. Researchers who retrieve artwork are not only researchers of humanities, but also researchers of materia...
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Liewu Cai, Lei Zhu, Hongyan Zhang and Xinghui Zhu
Cross-modal retrieval aims to search samples of one modality via queries of other modalities, which is a hot issue in the community of multimedia. However, two main challenges, i.e., heterogeneity gap and semantic interaction across different modalities,...
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Daniel Yang, Arya Goutam, Kevin Ji and TJ Tsai
This paper studies the problem of identifying piano music in various modalities using a single, unified approach called marketplace fingerprinting. The key defining characteristic of marketplace fingerprinting is choice: we consider a broad range of fing...
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Meng Jian, Jingjing Guo, Xin Fu, Lifang Wu and Ting Jia
The growing complex user intention gap and information overload are obstacles for users to access the desired content. User interactions and the involved content indicate rich evidence of users? interests. It is required to investigate interaction charac...
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Wei Wang, Ning Xu, Sina Dang, Xuefeng Hong and Jue Qu
In MR (mixed reality) environments, visual searches are often used for search and localization missions. There are some problems with search and localization technologies, such as a limited field of view and information overload. They are unable to satis...
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