Applied to Art and Design Scene Visual Comprehension and Recognition Algorithm Research

Combining advanced intelligent algorithms to improve the scene visual understanding and recognition method for art design can not only provide more inspirations and creative materials for artists, but also improve the efficiency and quality of art creation, and provide scientific and accurate references of artworks. Focusing on the art design scene visual understanding and recognition problem, a scene visual understanding and recognition method based on the intelligent optimisation algorithm to optimise the structural parameters of the multilayer perception machine is proposed. Firstly, the scene visual recognition method is outlined and analyzed, and the application scheme of multilayer perceptron in the understanding and recognition problem is designed; then, for the problems of the multilayer perceptron model, such as the training does not generalize, combined with the Pond's optimization algorithm, the training parameters of the multilayer perceptron model are optimized, and the visual understanding and recognition scheme of the art design scene is designed; finally, the proposed model is verified with the image dataset, and the scene visual understanding and recognition accuracy reaches 0.98, compared with other models, the proposed method has higher recognition accuracy. This research solves the problem of scene visual understanding and recognition, and applies it to the field of art design to improve the efficiency of art design assistance.

@article{Shi2024,
  title     = {Applied to Art and Design Scene Visual Comprehension and Recognition Algorithm Research},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {8},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Yuxin Shi},
  doi       = {10.14569/IJACSA.2024.0150809},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150809}
}