Samsung electronics co., ltd. (20240135697). ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF simplified abstract
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 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 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 20240135697 titled 'ELECTRONIC APPARATUS FOR IDENTIFYING A REGION OF INTEREST IN AN IMAGE AND CONTROL METHOD THEREOF
Simplified Explanation
The electronic apparatus described in the patent application includes a memory storing a neural network model with two networks, and a processor that processes images through these networks to generate new images and identify regions of interest. The neural network model is trained on sample images, corresponding description information, and regions of interest.
- The electronic apparatus includes a memory storing a neural network model with a first and second network.
- The processor processes images through the networks to generate new images and identify regions of interest.
- The neural network model is trained on sample images, description information, and regions of interest.
Potential Applications
This technology could be applied in various fields such as image processing, computer vision, and object recognition.
Problems Solved
This technology helps in generating new images based on input images and identifying regions of interest, which can be useful in tasks like image enhancement and object detection.
Benefits
The benefits of this technology include improved image processing capabilities, enhanced object recognition, and efficient identification of regions of interest in images.
Potential Commercial Applications
Potential commercial applications of this technology include image editing software, surveillance systems, and medical imaging tools.
Possible Prior Art
One possible prior art for this technology could be existing neural network models used for image processing and object recognition tasks.
Unanswered Questions
How does this technology compare to existing image processing techniques?
This article does not provide a direct comparison between this technology and existing image processing techniques. Further research or a comparative study would be needed to address this question.
What are the limitations of this technology in real-world applications?
The article does not discuss the limitations of this technology in real-world applications. Understanding the constraints and challenges faced by this technology would be crucial for its practical implementation.
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.
