Design Component Neural Network for UI Guideline Compliance
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Solution Overview
Problem
Existing interface-design systems face challenges in accurately and efficiently creating design components that comply with diverse user-interface guidelines for different computing platforms, requiring time-consuming manual adjustments and lacking automated categorization and modification capabilities.
Innovation Solution
A design-component-neural network is employed to categorize design components as platform widgets and validate them against user-interface guidelines, providing options to modify non-compliant components automatically, utilizing object-recognition and platform-component-recognition layers to generate design-feature indicators and determine compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual adjustment of design components is used to satisfy user-interface guidelines, then compliance accuracy is improved, but time consumption and productivity deteriorate
Solution Approach 1:
The system enables self-service by automatically detecting design components, categorizing them as platform widgets, and validating their properties against user-interface guidelines without requiring manual intervention. The neural network performs self-validation and self-correction, allowing the design system to service itself regarding compliance checking.
Solution Approach 2:
The patent replaces the mechanical manual adjustment process with an automated neural network system. The design-component-neural network substitutes human designers and developers in the compliance checking and adjustment process, using machine learning algorithms to detect, categorize, and validate design components automatically.
2Productivity
If automated validation using neural network is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The neural network system performs multiple functions within a single integrated architecture: object detection, design component identification, categorization as platform widgets, and validation against guidelines. This multi-functional approach consolidates what could be separate complex systems into one unified solution.
Solution Approach 2:
The design-component-neural network acts as an intermediary between the design component creation process and the user-interface guidelines compliance requirement. It mediates by automatically translating design components into categorized platform widgets and validating them, bridging the gap between design freedom and guideline compliance.
3Manufacturing precision
If detailed property validation is performed on design components, then compliance accuracy is improved, but detection and measurement difficulty increases
Solution Approach 1:
The patent replaces complex manual detection and measurement of design component properties with automated neural network analysis. The system uses machine learning to automatically extract, detect, and measure properties such as shape, shadowing, size, and other visual characteristics, converting complex analysis tasks into automated computational processes.
Solution Approach 2:
The neural network transforms the complexity of detailed property validation by changing the parameters of analysis from manual inspection to automated feature extraction. The system converts complex visual properties into quantifiable parameters that can be automatically compared against guideline requirements, simplifying the measurement process while maintaining precision.
Data Source
AI summary
This disclosure relates to methods, non-transitory computer readable media, and systems that use a design-component-neural network to categorize a design component from an interface-design file as a platform widget corresponding to a particular computing platform. Having categorized the design component as a platform widget, in certain implementations, the disclosed systems compare and validate properties of the design component against user-interface guidelines for the particular computing platform. Upon determining that the design component does not comply with a user-interface guideline, the systems can provide and implement options to modify the design component to comply with the user-interface guideline.