Deep Learning Approach to User Interface Enhancement and Web Quality Assurance

Abstract

"Within the field of web development, Web designing, Quality assurance testing and Usability Testing providing exceptional user experiences is crucial. Still, it can be difficult to recognize and resolve problems with UI design, front-end development, and quality assurance. This study offers a comprehensive approach to address these issues by automating the analysis of web components using screenshots and offering helpful details and suggestions for improving the usability, accessibility, and general user experience. The technology effectively recognizes web components and carries out thorough evaluations to find possible areas for development using cutting-edge deep learning techniques. By using an inventive method, the system is quite effective at recognizing web elements from PNG screenshots and offers insightful information about the online environment. It is important to note that it uses deep learning methods to improve its ability to recognize objects like buttons, photos, URLs, iframes, and more. The interface is thoroughly understood by the system through the composition and layout analysis of web pages, which helps it recognize possible issues with accessibility and usability. The technology helps web designers, and web developers to improve their digital products and make sure they closely match consumer expectations by providing them with practical advice based on data analysis. Developers can prioritize enhancements that lead to significant engagement and satisfaction by focusing on the fundamental components of web design and user experience. In the end, this strategy supports a culture of continuous improvement where small enhancements to web applications are guided by user input and data-driven insights."