HyNet: A novel hybrid deep learning approach for efficient interior design texture retrieval

Abstract Interior designers are suffering from a lack of intelligent design methods. This study aims to enhance the accuracy and efficiency retrieval textures for interior design, which is crucial step toward design. Currently, rely on repetitive tasks obtain websites, ineffective as often requires hundreds textures. To address this issue, proposes hybrid deep learning approach, HyNet, boosts by recommending similar instead blindly searching. Additionally, new indoor texture dataset created support application artificial intelligence in field. The results demonstrate that proposed method’s ten recommended images achieve high rate 91.41%. significant improvement efficiency, can facilitate industry’s progression towards intelligence. Overall, offers promising solution challenges facing designers, it has potential significantly productivity innovation.