Map-Based AI Model Loading for Object Recognition Control
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Solution Overview
Problem
Electronic devices face limitations in object recognition capabilities due to high memory and processing requirements, especially when using advanced artificial intelligence models for accurate object recognition across various environments.
Innovation Solution
An electronic apparatus is designed with a sensor, camera, and storage to determine its location on a map, selectively loading appropriate artificial intelligence models from a storage to a volatile memory for efficient object recognition, using a first processor to identify the area and a second processor for object recognition tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advanced artificial intelligence models are used for accurate object recognition, then object recognition capability is improved, but memory capacity and processing capability requirements increase significantly
Solution Approach 1:
The patent segments the object recognition system by dividing it into a lightweight object detection model for initial identification and a more comprehensive artificial intelligence model for detailed recognition. This segmentation allows the device to use only the necessary processing power and memory for each specific task, reducing overall memory capacity requirements while maintaining accurate object recognition capability.
2Measurement precision
If advanced artificial intelligence models are used for accurate object recognition, then object recognition capability is improved, but processing capability requirements increase significantly
Solution Approach 1:
The patent segments the object recognition system by dividing it into a lightweight object detection model for initial identification and a more comprehensive artificial intelligence model for detailed recognition. This segmentation allows the device to use only the necessary processing power and memory for each specific task, reducing overall processing capability requirements while maintaining accurate object recognition capability.
Solution Approach 2:
The patent applies partial action by using a lightweight object detection model that performs only the essential function of identifying and locating objects in an image. This partial recognition approach processes only the necessary information for basic object detection, reducing processing capability requirements compared to using a full-featured AI model for all recognition tasks.
3Adaptability or versatility
If comprehensive artificial intelligence models are deployed to recognize various objects, then object recognition versatility is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamics by making the AI model selection adaptive based on the detected object type. The system dynamically selects which comprehensive AI model to deploy depending on what objects are detected in the environment. This dynamic approach allows the device to maintain versatility for recognizing various objects while reducing model management complexity by only loading and managing the specific AI models needed for currently detected objects.
Data Source
AI summary
An electronic apparatus is disclosed. The electronic apparatus includes a sensor, a camera, a memory, a camera and a processor. The memory stores a plurality of artificial intelligence models trained to identify objects and stores information on a map. The first processor provides, to the second processor, area information on an area in which the electronic apparatus is determined, based on sensing data obtained from the sensor, to be located, from among a plurality of areas included in the map. The second processor loads at least one artificial intelligence model of the plurality of artificial intelligence models to the volatile memory based on the area information and identifies an object by inputting the image obtained through the camera to the loaded artificial intelligence model.