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Applied Sciences, 2023 Cross-modal sentiment analysis is an emerging research area in natural language processing. The core task of cross-modal fusion lies in cross-modal relationship extraction and joint feature learning. The existing research methods of cross-modal sentiment
Ping He +3 more
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Deep Label Feature Fusion Hashing for Cross-Modal Retrieval
IEEE Access, 2022 The rapid growth of multi-modal data in recent years has driven the strong demand for retrieving semantic-related data within different modalities. Therefore, cross-modal hashing has attracted extensive interest and studies due to its fast retrieval ...
Dongxiao Ren +3 more
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Cross-Modal Representation [PDF]
, 2020 AbstractCross-modal representation learning is an essential part of representation learning, which aims to learn latent semantic representations for modalities including texts, audio, images, videos, etc. In this chapter, we first introduce typical cross-modal representation models. After that, we review several real-world applications related to cross-
Zhiyuan Liu, Yankai Lin, Maosong Sun
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Frontiers in Neurorobotics, 2020 The emergence of cross-modal learning capabilities requires the interaction of neural areas accounting for sensory and cognitive processing. Convergence of multiple sensory inputs is observed in low-level sensory cortices including primary somatosensory (
Xiaxia Xu +2 more
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Cross-Modal Manifold Learning for Cross-modal Retrieval
, 2016 This paper presents a new scalable algorithm for cross-modal similarity preserving retrieval in a learnt manifold space. Unlike existing approaches that compromise between preserving global and local geometries, the proposed technique respects both simultaneously during manifold alignment.
Conjeti, Sailesh +3 more
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Literature Review of Cross-Modal Retrieval Research
Jisuanji kexue yu tansuo, 2021 With the vigorous development of Internet technology and the popularization of smart devices, while the amount of multimedia data exploding, their forms become increasingly diverse. People's demand for information is no longer satisfied with single-modal
CHEN Ning, DUAN Youxiang, SUN Qifeng
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SensorsFine-grained representation is fundamental to species classification based on deep learning, and in this context, cross-modal contrastive learning is an effective method.
Rui Tao, Meng Zhu, Haiyan Cao, Honge Ren
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Cross-modal communication technology: A survey
Fundamental ResearchIn the 5G era and beyond, multi-modal services that integrate audio, visual, and haptic signals are expected to become dominant applications. To support multi-modal services, the concept of cross-modal communications, which involves collaborative audio ...
Xin Wei +3 more
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Cross-Modal Health State Estimation [PDF]
Proceedings of the 26th ACM international conference on Multimedia, 2018 Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18 ...
Nag, Nitish +5 more
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Metaplasticity framework for cross-modal synaptic plasticity in adults
Frontiers in Synaptic Neuroscience, 2023 Sensory loss leads to widespread adaptation of neural circuits to mediate cross-modal plasticity, which allows the organism to better utilize the remaining senses to guide behavior.
Hey-Kyoung Lee
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