Machine learningDeep learning / NLP / CV

Multimodal Multilayer Perceptron

A Multimodal Multilayer Perceptron (MM-MLP) is a feedforward neural network that ingests features from two or more heterogeneous input modalities — such as structured tabular data, text embeddings, and image feature vectors — by encoding each stream separately and fusing them into a shared representation before passing it through fully connected layers to produce a classification or regression output.

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Sources

  1. Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., & Ng, A. Y. (2011). Multimodal deep learning. In Proceedings of the 28th International Conference on Machine Learning (ICML 2011), pp. 689–696. link
  2. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning (Ch. 6: Deep Feedforward Networks). MIT Press. ISBN: 978-0-262-03561-3

Related methods

ScholarGateMultimodal Multilayer Perceptron (Multimodal Multilayer Perceptron (MM-MLP)). Retrieved 2026-06-04 from https://scholargate.app/tr/deep-learning/multimodal-multilayer-perceptron