Due to the rapid development of Internet multimedia technology, the wide use of smart phones and the expansion of social networks, people can share interesting content on the Internet anytime and anywhere, makes the different mode of multimedia data on the Internet (such as text, images and video, etc.) to present the characteristics of explosive growth, huge amounts of agglomeration. Such large-scale data marks the arrival of the era of multimedia big data, and brings new oortunities and challenges to the research and alication based on multi-modal learning. This paper focuses on the cross-modal research of neural networks fused with multimedia retrieval. This paper first analyzes the basic models of machine learning and neural networks, and proposes a cross-modal multimedia semantic matching method. The simulation results show that the proposed multi-media retrieval cross-modal neural network model has certain effectiveness and feasibility.

Kothapalli Radhakrishnan. Cross-modal Neural Networks Fused with Multimedia Retrieval. International Journal of Neural Network (2021), Vol. 2, Issue 2: 40-46. https://doi.org/10.38007/NN.2021.020206.

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