aspg-18-3690-1792524076 20261020192116 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Intelligent Systems and Internet of Things JISIoT 2769-786X 2690-6791 2025 16 2 Wei Zou University of Science Malaysia, Penang, 11700, Malaysia Mohd Alif Ikrami Bin Mutti University of Science Malaysia, Penang, 11700, Malaysia Nixi black pottery has a unique place in Chinese black pottery art. In this article, we have developed a style transfer model based on deep learning, which automatically transforms Nixi black pottery into images of other styles. This is of great value for the dissemination of this art. In this paper, we propose a method called DualTrans that utilizes a pure Transformer architecture to enable context-aware image processing, effectively addressing the issue of low receptive field. Additionally, we introduce a Location Information Encoding Module (LIM) and a Style Transfer Control Module (STCM) to tackle the problem of long-range dependencies while ensuring that the generated target image remains structurally and stylistically consistent throughout the style transfer process, without being influenced by the content and style images. During the mapping process, the LIM encodes the original image block information and concatenates it with the projected image block information. To alter the final produced style of the picture, the STCM leverages a set of learnable style-controllable factors. Extensive trials have shown that DualTrans exceeds previous approaches in terms of stability. 2025 117 122 3690 https://creativecommons.org/licenses/by/4.0/ 10.54216/JISIoT.160209 https://www.americaspg.com/journal/18/article/3690 https://www.americaspg.com/storage/61741961376.pdf