17926850. MACHINE LEARNING DEVICE simplified abstract (SUBARU CORPORATION)
Contents
MACHINE LEARNING DEVICE
Organization Name
Inventor(s)
MACHINE LEARNING DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 17926850 titled 'MACHINE LEARNING DEVICE
The abstract describes a machine learning device that can detect road surfaces and generate distance images using captured images.
- Road surface detection processor identifies road surfaces in captured images.
- Distance value selector chooses distance values for processing based on road surface detection results.
- Learning processor creates a learning model for generating distance images from new captured images using machine learning.
Potential Applications: - Autonomous driving systems - Road maintenance and construction - Traffic flow optimization
Problems Solved: - Accurate road surface detection - Efficient distance image generation - Enhancing machine learning capabilities in image processing
Benefits: - Improved road safety - Enhanced navigation systems - Increased efficiency in road maintenance
Commercial Applications: Title: "Advanced Machine Learning Device for Road Surface Detection" This technology can be utilized in autonomous vehicles, smart city infrastructure, and transportation planning, offering innovative solutions for road safety and maintenance.
Questions about the technology: 1. How does this machine learning device improve road surface detection compared to traditional methods? 2. What are the potential challenges in implementing this technology on a large scale?
Frequently Updated Research: Stay updated on advancements in machine learning algorithms for image processing and road surface detection to enhance the capabilities of this device.
Original Abstract Submitted
A machine learning device according to an embodiment of the disclosure includes: a road surface detection processor configured to detect, on the basis of a first captured image and a first distance image depending on the first captured image, a road surface included in the first captured image; a distance value selector configured to select one or more distance values to be processed, from among distance values included in the first distance image, on the basis of a processing result of the road surface detection processor; and a learning processor configured to generate a learning model to be supplied with a second captured image and to output a second distance image depending on the second captured image, by carrying out machine learning processing on the basis of the first captured image and the one or more distance values.
