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Cross-modal neuroplasticity in partial hearing loss: a mini-review [PDF]
Frontiers in NeuroscienceSensory loss induces adaptive neural changes in the remaining non-deprived senses, known as cross-modal plasticity. Recent proposals of cross-modal plasticity suggest that it is a top-down, dynamic phenomenon that can occur through the lifespan and is ...
Patricia V. Aguiar +2 more
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Flexible Cross-Modal Hashing [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 Hashing has been widely adopted for large-scale data retrieval in many domains due to its low storage cost and high retrieval speed. Existing cross-modal hashing methods optimistically assume that the correspondence between training samples across modalities is readily available. This assumption is unrealistic in practical applications.
Guoxian Yu +4 more
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Survey of Research Progress on Cross-modal Retrieval [PDF]
Jisuanji kexue, 2021 With the explosive growth of multimedia data on the Internet,single-modal retrieval has been unable to meet the needs of users,and cross-modal retrieval has emerged.Cross-modal retrieval aims to retrieve related data of one modality with data of another ...
FENG Xia, HU Zhi-yi, LIU Cai-hua
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Survey of Research on Deep Learning Image-Text Cross-Modal Retrieval [PDF]
Jisuanji kexue yu tansuo, 2022 As the rapid development of deep neural networks, multi-modal learning techniques are widely concerned. Cross-modal retrieval is an important branch of multimodal learning. Its fundamental purpose is to reveal the relation between different modal samples
LIU Ying, GUO Yingying, FANG Jie, FAN Jiulun, HAO Yu, LIU Jiming
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Deep Multi-Semantic Fusion-Based Cross-Modal Hashing
Mathematics, 2022 Due to the low costs of its storage and search, the cross-modal retrieval hashing method has received much research interest in the big data era. Due to the application of deep learning, the cross-modal representation capabilities have risen markedly ...
Xinghui Zhu +3 more
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Cross-Modal Scene Networks [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018 See more at http://cmplaces.csail.mit.edu/.
Yusuf Aytar +4 more
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Diachronic Cross-modal Embeddings [PDF]
Proceedings of the 27th ACM International Conference on Multimedia, 2019 Understanding the semantic shifts of multimodal information is only possible with models that capture cross-modal interactions over time. Under this paradigm, a new embedding is needed that structures visual-textual interactions according to the temporal dimension, thus, preserving data's original temporal organisation.
Semedo, David, Magalhães, João
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Attentive Cross-Modal Paratope Prediction [PDF]
Journal of Computational Biology, 2019 Antibodies are a critical part of the immune system, having the function of directly neutralising or tagging undesirable objects (the antigens) for future destruction. Being able to predict which amino acids belong to the paratope, the region on the antibody which binds to the antigen, can facilitate antibody design and contribute to the development of
Deac, Andreea +2 more
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A Survey of Full-Cycle Cross-Modal Retrieval: From a Representation Learning Perspective
Applied Sciences, 2023 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 ...
Suping Wang +4 more
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CMBF: Cross-Modal-Based Fusion Recommendation Algorithm
Sensors, 2021 A recommendation system is often used to recommend items that may be of interest to users. One of the main challenges is that the scarcity of actual interaction data between users and items restricts the performance of recommendation systems.
Xi Chen +3 more
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