18487374. METHOD OF TRAINING OBJECT RECOGNITION MODEL BY USING SPATIAL INFORMATION AND COMPUTING DEVICE FOR PERFORMING THE METHOD simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
- 1 METHOD OF TRAINING OBJECT RECOGNITION MODEL BY USING SPATIAL INFORMATION AND COMPUTING DEVICE FOR PERFORMING THE METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD OF TRAINING OBJECT RECOGNITION MODEL BY USING SPATIAL INFORMATION AND COMPUTING DEVICE FOR PERFORMING THE 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
METHOD OF TRAINING OBJECT RECOGNITION MODEL BY USING SPATIAL INFORMATION AND COMPUTING DEVICE FOR PERFORMING THE METHOD
Organization Name
Inventor(s)
Jinyoung Hwang of Suwon-si (KR)
METHOD OF TRAINING OBJECT RECOGNITION MODEL BY USING SPATIAL INFORMATION AND COMPUTING DEVICE FOR PERFORMING THE METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18487374 titled 'METHOD OF TRAINING OBJECT RECOGNITION MODEL BY USING SPATIAL INFORMATION AND COMPUTING DEVICE FOR PERFORMING THE METHOD
Simplified Explanation
The abstract describes a method of training an object recognition model using spatial information, including illumination information, to obtain training data and train a neural network model for object recognition.
- Obtaining spatial information, including illumination information, for multiple spots in a space.
- Obtaining illumination information for at least one spot from the spatial information.
- Obtaining training data using the illumination information and an image captured from the spot.
- Training a neural network model for object recognition using the training data.
Potential Applications
This technology could be applied in various fields such as autonomous vehicles, surveillance systems, and robotics for improved object recognition capabilities.
Problems Solved
This technology addresses the challenge of training object recognition models with spatial information, specifically illumination data, to enhance the accuracy and performance of the models.
Benefits
The use of spatial information, including illumination data, can lead to more robust and accurate object recognition models, improving overall system performance and reliability.
Potential Commercial Applications
Potential commercial applications of this technology include security systems, industrial automation, and smart home devices that require advanced object recognition capabilities.
Possible Prior Art
One possible prior art could be the use of spatial information in training object recognition models, but the specific incorporation of illumination information for training data may be a novel aspect of this technology.
What are the specific spatial information used in the training data?
The specific spatial information used in the training data includes illumination information corresponding to multiple spots in a space, which is then utilized to train the neural network model for object recognition.
How does the incorporation of illumination information improve object recognition accuracy?
The incorporation of illumination information helps the neural network model learn to recognize objects under different lighting conditions, leading to improved accuracy in object recognition tasks.
Original Abstract Submitted
A method of training an object recognition model by using spatial information is provided. The method includes obtaining spatial information including illumination information corresponding to a plurality of spots in a space, obtaining illumination information corresponding to at least one spot of the plurality of spots from the spatial information, obtaining training data by using the obtained illumination information and an image obtained by capturing the at least one spot, and training a neural network model for object recognition by using the training data.
