Machine-Learning Image Analysis for Automatic Method Selection
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Solution Overview
Problem
Users face challenges in selecting the appropriate analytical method for image analysis due to storage capacity and computing time constraints, especially when images contain minimal information without additional context, and existing software solutions are cumbersome to manage.
Innovation Solution
A machine learning master-algorithm trained on images and analytical methods selects a suitable analysis-algorithm for image analysis, allowing efficient image analysis across various materials, including construction materials, by determining the appropriate method based on the image content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple software programs are used for different analytical problems, then the suitability for specific analytical tasks is improved, but storage capacity and device complexity increase
Solution Approach 1:
The patent implements a universal image analysis system that can perform multiple analytical tasks through a single software interface. The system uses a machine learning master-algorithm that automatically selects and executes appropriate analysis methods based on the input image characteristics, eliminating the need for multiple specialized software programs while maintaining adaptability to different analytical problems
Solution Approach 2:
The system employs self-service mechanisms where the machine learning master-algorithm autonomously determines the appropriate analysis method without user intervention. The algorithm automatically selects from multiple analysis approaches based on image features, reducing the complexity of user decision-making while maintaining task suitability
2Adaptability or versatility
If multiple software programs are installed for different analytical problems, then the capability to solve specific problems is improved, but computing time for selection and operation increases
Solution Approach 1:
The system performs preliminary action by pre-training the machine learning master-algorithm on diverse image data and analysis methods. This pre-training enables the algorithm to quickly and accurately select appropriate analysis methods without requiring time-consuming runtime decisions, thus reducing computing time while maintaining problem-solving capability
Solution Approach 2:
The patent replaces the mechanical system of manual software selection with an automated machine learning-based selection process. The master-algorithm uses image feature extraction and classification to automatically determine the appropriate analysis method, eliminating the time required for user decision-making and manual software switching
3Ease of operation
If users manually select analytical methods based on images with minimal information, then method selection capability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent introduces an intermediary machine learning master-algorithm that mediates between the input image and the analysis method selection. This intermediary automatically interprets image features and translates them into appropriate method selections, eliminating the difficulty users would face in manually determining the correct analysis approach from minimal image information
Data Source
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AI summary
The present invention is related to computer-implemented methods for the analysis of images. Methods of the present invention include a step of selecting, by a machine learning master-algorithm, at least one analysis-algorithm suitable for a particular analytical problem, said machine learning master-algorithm being trained to determine which analysis-algorithm is suitable for analyzing a given digital image of an analyte.