Color Intelligent Analysis Based on Deep Learning

Intelligent colour analysis based on deep learning has a wide range of applications in image, video, and other colour information automatic analysis and understanding and has great potential. Deep learning models can learn the representation of color features through the process of feature abstraction and hierarchical extraction and feature learning to express colors, as well as pattern recognition that is suitable for the given task. They have stronger feature representation, learning, and generalization abilities. These characteristics allow deep learning models to better deal with the problems incurred by traditional methods in the processing, analysis, and understanding of colour and its features. The author mainly uses Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to analyse and process color data through the designed experimental system, respectively. The learning process of deep learning model is fully automatic, and the representation and abstraction ability of the model is improved through the large-scale annotated data. It can be used in the field of image/video recognition and understanding of color by deep learning method. The experimental results are shown in this paper. The application of deep learning-based color intelligent analysis in different tasks has achieved remarkable results. A deep learning model can accurately analyse the color and color texture of the image and its distribution in the image, and be used in the image recognition and classification task.