18367193. ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF simplified abstract (Samsung Electronics Co., Ltd.)
Contents
- 1 ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Image Analysis Technology
- 1.13 Original Abstract Submitted
ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF
Organization Name
Inventor(s)
Wookhyung Kim of Suwon-si (KR)
ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 18367193 titled 'ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF
Simplified Explanation
An electronic apparatus with a memory stores a neural network model with two networks. The processor uses this model to analyze images and identify regions of interest.
- The electronic apparatus stores a neural network model with two networks.
- The processor analyzes images using this model.
- Regions of interest in the images are identified.
Key Features and Innovation
- Memory stores a neural network model with two networks.
- Processor analyzes images to identify regions of interest.
- Model trained on sample images, description information, and regions of interest.
Potential Applications
This technology can be used in image recognition, object detection, and medical imaging to identify specific areas of interest in images.
Problems Solved
This technology addresses the challenge of efficiently identifying regions of interest in images, improving image analysis accuracy and speed.
Benefits
- Enhanced image analysis capabilities.
- Improved accuracy in identifying regions of interest.
- Faster processing of images.
Commercial Applications
Title: Advanced Image Analysis Technology for Various Industries This technology can be applied in industries such as healthcare, security, and manufacturing for tasks like medical diagnosis, surveillance, and quality control.
Prior Art
Researchers can explore prior art related to neural networks, image analysis, and object detection to understand the evolution of similar technologies.
Frequently Updated Research
Researchers are constantly improving neural network models for image analysis, leading to advancements in various fields such as autonomous vehicles and robotics.
Questions about Image Analysis Technology
1. How does this technology improve image analysis accuracy? This technology enhances accuracy by using neural networks to identify regions of interest in images. 2. What are the potential applications of this technology in healthcare? This technology can be used in medical imaging for tasks like identifying specific areas of interest in diagnostic images.
Original Abstract Submitted
An electronic apparatus includes a memory configured to store a neural network model including a first network and a second network. The electronic apparatus also includes at least one processor connected to the memory. The at least one processor is configured to obtain description information corresponding to a first image by inputting the first image to the first network, obtain a second image based on the description information, obtain a third image representing a region of interest of the first image by inputting the first image and the second image to the second network. The neural network model is a model trained based on a plurality of sample images, a plurality of sample description information corresponding to the plurality of sample images, and a sample region of interest of the plurality of sample images.
