Abstract
In this study, we propose a novel approach, "Supervised Generative Forming," which generates and manipulates images while reflecting the creator's intent through the integration of interactive artificial intelligence with image recognition technology. In conventional generative art, deriving rules from the desired final shape has posed a significant challenge. However, this system provides visual feedback at each stage of rule application. This approach enables the rules to be adjusted incrementally to achieve a gradual convergence between the initial state and the
desired final shape. This approach facilitates the development of sophisticated models that preserve the organic
shapes observed in nature while enabling creators to maintain oversight during the design process.
