Recognition Specialized Sensor Adaptive Pixel Reading Control
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Solution Overview
Problem
The recognition specialized sensor has a different configuration and requires different training and evaluation data compared to general recognizers, limiting its application.
Innovation Solution
An information processing apparatus that generates control information for a recognition process using a second recognizer based on a dataset or a first recognizer trained with a first signal from a first sensor, allowing for compatibility between different sensor types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a recognition specialized sensor controls a pixel reading unit to suppress processing time and power consumption, then processing time and power consumption are reduced, but the configuration becomes greatly different from general recognizers, limiting application scope
Solution Approach 1:
The patent enables the recognition specialized sensor to process both specialized training data and general training data by configuring the pixel reading unit control section to adaptively control pixel reading based on the input data type. This allows the same sensor hardware to serve multiple recognition purposes, achieving universality without requiring separate specialized sensors for different applications.
Solution Approach 2:
The patent changes the operational parameters of the pixel reading unit based on the type of recognition process being performed. For specialized recognition, pixels are read in a first reading pattern optimized for specialized data, while for general recognition, pixels are read in a second reading pattern suitable for general training data. This parameter adaptation allows the sensor to maintain high efficiency while broadening its application scope.
2Productivity
If a recognition specialized sensor uses a different pixel reading unit control configuration, then processing efficiency is improved, but compatibility with general training data and evaluation data is reduced
Solution Approach 1:
The patent implements a dynamic pixel reading unit control mechanism that adapts its reading pattern based on the type of data being processed. The control section dynamically switches between a first reading pattern for specialized data and a second reading pattern for general data, allowing the system to maintain optimal processing efficiency for each data type while ensuring broad compatibility.
Solution Approach 2:
By designing the pixel reading unit to support multiple reading patterns, the patent makes the recognition specialized sensor universally applicable to both specialized and general recognition tasks. The same hardware infrastructure handles different data types through configurable reading strategies, eliminating the need for separate specialized hardware for different data formats.
3Measurement precision
If the recognition specialized sensor is designed for specific recognition tasks, then recognition accuracy for specialized data is improved, but the sensor cannot effectively process general training and evaluation data
Solution Approach 1:
The patent employs dynamic control of the pixel reading unit that adjusts its operation based on the data type being processed. For specialized data, the reading unit operates in a mode optimized for high recognition accuracy on specialized patterns. For general data, it switches to a mode that ensures compatibility with standard training and evaluation datasets, thus maintaining both specialization and adaptability.
Solution Approach 2:
The patent changes operational parameters of the pixel reading unit based on data type. The control section modifies reading patterns, pixel selection criteria, and data acquisition strategies according to whether the input is specialized or general data, allowing the sensor to optimize accuracy for its specialized function while remaining capable of processing general data effectively.
Data Source
AI summary
An information processing apparatus according to an embodiment includes a generation part (301) that generates, based on a dataset (300, 303) or a first recognizer (310) for training the first recognizer that performs a recognition process based on a first signal read from a first sensor, control information (313) for controlling a recognition process by a second recognizer (312) that performs the recognition process based on a second signal read from a second sensor having a reading unit different from the first sensor.