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Multimodal Machine Learning Applications

Multimodal Machine Learning Applications is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 22k research works in it since 1975. 9.6% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the development and improvement of visual question answering systems, image captioning techniques, and neural networks for understanding and generating descriptions of images and videos. The research involves semantic reasoning, multimodal fusion, scene graph generation, attention mechanisms, and deep learning approaches to bridge the gap between vision and language.

  • Visual Question Answering
  • Image Captioning
  • Neural Networks
  • Semantic Reasoning
  • Multimodal Fusion
  • Scene Graph Generation
  • Video Description
  • Attention Mechanism
  • Language Understanding
  • Deep Learning
Research works
22k
fractional, since 1975
In the world top 10%
2.1k
per year above
Top-10% rate
9.6%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+106%
the tick is no change
Largest producer
China
56% of the 10 largest, 2022-now
Multimodal Machine Learning Applications

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