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With the rapid development of artificial intelligence (AI) and cognitive computing, an increasing number of disciplines have begun to innovate with these technologies, especially in artistic creation (Anantrasirichai & Bull, 2022). In traditional artistic creation, the application of technology is still in an auxiliary position, and the artist’s creativity and emotional expression are the core (Li et al., 2024; Zhang & Lei, 2025). However, with the introduction of AI technologies such as cognitive computing and deep learning, the ways art is created have undergone profound changes (Chatterjee, 2022; Shen & Yu, 2021). AI not only can provide technical support, but also can begin to participate in artistic expression and style shaping, becoming a “collaborator” in artistic creation (Chen, 2024; Lee & Chen, 2024). Especially in the field of ceramic art, the combination of AI and cognitive computing provides a new creative mode for this traditional process, and promotes the intelligent and digital transformation of ceramic art.
As a traditional art form with profound cultural heritage, ceramic art has experienced thousands of years of development. Its creation depends on exquisite technology and artists’ subjective creativity (Guanqing & Qifu, 2024; Nie, 2025). Nevertheless, with the continuous changes in the way art is created around the globe, ceramic art is also facing many challenges, especially in the bottleneck of creative efficiency and artistic expression. The traditional ceramic creation technique is often limited by the manual process, and it is difficult to complete complex designs in a short time or to switch freely between a variety of artistic styles. With the rise of computer vision, deep learning, and cognitive computing technologies, AI has gradually entered the field of ceramic design, showing great potential, especially in the processing and generation of ceramic images.
At present, the application of AI, especially in the field of computer vision, has made remarkable progress in many areas of artistic creation (Santos et al., 2021). By using deep learning models, such as convolutional neural networks (CNN) and generative adversarial networks, AI can achieve artistic style transfer, image generation, and analysis, which provides a new creative tool for ceramic art. However, although AI has shown good results in general artistic creation, there are still many challenges in the specific application of ceramic art. Traditional image processing technology cannot fully express the material details, cultural symbols, and artistic values of ceramic works in ceramic art creation. Most of the existing generation models are limited to the generation of two-dimensional images, and it is difficult to realize the three-dimensional sense and complexity of ceramic works with such models. Furthermore, although the artistic works generated by AI are highly accurate in technology, they often lack emotional and cultural communication. There is still a great gap between the emotional depth of AI and that of traditional artistic creation.
In order to meet these challenges, this paper proposes a ceramic image processing method that combines deep feature extraction, multi-instance learning, and cognitive computing. By introducing multi-scale feature extraction and attention mechanisms, the proposed method can simulate the human visual perception process and improve the accurate expression of image features. In addition, the ceramic art generation method proposed in this paper is based on 3D image reconstruction technology that allows it to break through the two-dimensional limitation of the traditional generation model, realizing three-dimensional reconstruction and virtual generation of ceramic works, thus providing a new technical means for ceramic art creation.