18273278. INFORMATION PROCESSING DEVICE, AND SELECTION OUTPUT METHOD simplified abstract (Mitsubishi Electric Corporation)
Contents
- 1 INFORMATION PROCESSING DEVICE, AND SELECTION OUTPUT METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INFORMATION PROCESSING DEVICE, AND SELECTION OUTPUT METHOD - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
INFORMATION PROCESSING DEVICE, AND SELECTION OUTPUT METHOD
Organization Name
Mitsubishi Electric Corporation
Inventor(s)
INFORMATION PROCESSING DEVICE, AND SELECTION OUTPUT METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18273278 titled 'INFORMATION PROCESSING DEVICE, AND SELECTION OUTPUT METHOD
Simplified Explanation
The patent application describes an information processing device that uses multiple learned models to perform object detection on unlabeled learning data, calculates information amount scores based on the detection results, and selects a predetermined number of pieces of learning data for further processing.
- Acquisition unit acquires learned models for object detection
- Object detection unit performs detection on unlabeled learning data using learned models
- Calculation unit calculates information amount scores based on detection results
- Selection output unit selects pieces of learning data based on information amount scores
Potential Applications
This technology can be applied in various fields such as autonomous driving, surveillance systems, and industrial automation for efficient object detection and recognition.
Problems Solved
This technology solves the problem of efficiently processing large amounts of unlabeled learning data for object detection tasks, improving the accuracy and speed of detection systems.
Benefits
The benefits of this technology include improved object detection accuracy, faster processing of learning data, and increased efficiency in handling large datasets.
Potential Commercial Applications
One potential commercial application of this technology is in the development of advanced security systems for public spaces, where quick and accurate object detection is crucial for ensuring safety.
Possible Prior Art
One possible prior art for this technology could be the use of machine learning algorithms for object detection in image processing applications.
Unanswered Questions
How does this technology compare to existing object detection methods in terms of accuracy and efficiency?
This article does not provide a direct comparison with existing object detection methods, so it is unclear how this technology performs in relation to other approaches.
What are the limitations of this technology in handling complex or dynamic environments for object detection?
The article does not address the potential limitations of this technology in scenarios where objects are in complex or dynamic environments, leaving room for further exploration of its capabilities in such conditions.
Original Abstract Submitted
An information processing device includes an acquisition unit that acquires learned models for executing object detection by methods different from each other and a plurality of pieces of unlabeled learning data as a plurality of images including an object, an object detection unit that performs the object detection on each of the plurality of pieces of unlabeled learning data by using the learned models, a calculation unit that calculates a plurality of information amount scores indicating values of the plurality of pieces of unlabeled learning data based on a plurality of object detection results, and a selection output unit that selects a predetermined number of pieces of unlabeled learning data from the plurality of pieces of unlabeled learning data based on the plurality of information amount scores and outputs the selected unlabeled learning data.
