Among the information that humans obtain daily, humans recognize things and transform the world through visual senses. The advantage of visual information makes its memory more durable than other information carriers, and the information contained in the image itself is more intuitive and vivid, and hidden behind the image features is rich human emotional semantic information. Therefore, this paper studies and analyzes image emotion recognition (IER) based on fuzzy neural network(FNN). This paper firstly introduces the two basic concepts of FNN and image emotion feature, and then studies emotion recognition methods such as the overall framework of IER, selective joint fine-tuning strategy and multi-feature extraction, and finally the emotion recognition method. Coefficient and selective joint fine-tuning strategies are analyzed and conclusions are drawn.

Rui Feng. Image Emotion Recognition Supporting Fuzzy Neural Network. International Journal of Neural Network (2021), Vol. 2, Issue 4: 49-55. https://doi.org/10.38007/NN.2021.020407.

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