Edge Device Model Delivery with Imaging Conditions
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Solution Overview
Problem
In edge devices equipped with photodetectors, varying conditions can lead to suboptimal inference accuracy in image recognition and classification processing, as existing systems only deliver trained models without considering the specific imaging conditions used during model generation.
Innovation Solution
An integrated management apparatus that associates and delivers trained models with their corresponding imaging conditions to edge devices, ensuring that inference is performed under the same conditions used for model training, thereby improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If trained models are delivered to edge devices without associated imaging conditions, then device complexity is reduced and deployment is simplified, but inference accuracy deteriorates due to mismatched imaging conditions
Solution Approach 1:
The patent combines the trained model and its corresponding imaging conditions into a single integrated package that is delivered together to edge devices. This merging ensures that the model receives all necessary condition information (exposure time, gain, illumination intensity, etc.) required for accurate inference, thereby resolving the accuracy deterioration issue while maintaining manageable complexity through unified delivery.
Solution Approach 2:
The patent introduces an integrated management apparatus as an intermediary between model training systems and edge devices. This intermediary manages the association between models and imaging conditions, and facilitates their coordinated delivery to edge devices, simplifying the overall system architecture while ensuring accurate model deployment with all necessary parameters.
2Measurement precision
If imaging conditions are not maintained consistently with model training conditions, then adaptability to different edge device conditions is improved, but measurement precision deteriorates due to blurriness or overexposure
Solution Approach 1:
The patent delivers specific imaging condition parameters (exposure time, gain, illumination intensity) along with the trained model to edge devices. These parameter changes ensure that the imaging conditions during inference match the training conditions, maintaining measurement precision. The system adapts to different edge devices by adjusting these parameters according to the specific model requirements.
3Loss of information
If multiple edge devices with varying conditions are managed separately, then ease of operation is improved for device-specific configurations, but loss of information increases due to inability to track condition-model associations
Solution Approach 1:
The integrated management apparatus provides universal functionality to manage multiple edge devices with varying conditions. It maintains a centralized repository that stores associations between models and imaging conditions, and delivers the appropriate combinations to any edge device. This universal approach prevents information loss while simplifying operation through a single management interface.
Data Source
AI summary
A system includes one or more edge devices an integrated management apparatus configured to manage the one or more edge devices. The edge devices include a photodetector. The integrated management apparatus manages a first trained model and a first condition in association with each other. The first condition sets a condition for a photodetector used in generating the first trained model. The integrated management apparatus is configured to deliver the first trained model and the first condition to the edge devices.