Boe technology group co., ltd. (20240203097). METHOD AND APPARATUS FOR TRAINING IMAGE PROCESSING MODEL, AND IMAGE CLASSIFYING METHOD AND APPARATUS simplified abstract
METHOD AND APPARATUS FOR TRAINING IMAGE PROCESSING MODEL, AND IMAGE CLASSIFYING METHOD AND APPARATUS
Organization Name
boe technology group co., ltd.
Inventor(s)
Zeyu Shangguan of Beijing (CN)
METHOD AND APPARATUS FOR TRAINING IMAGE PROCESSING MODEL, AND IMAGE CLASSIFYING METHOD AND APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240203097 titled 'METHOD AND APPARATUS FOR TRAINING IMAGE PROCESSING MODEL, AND IMAGE CLASSIFYING METHOD AND APPARATUS
The abstract describes a method for training an image processing model, involving acquiring original image sets, cropping images to create a training sample set, determining positive and negative sample pairs, and training the model based on these pairs.
- Acquiring original image sets
- Cropping images to create a training sample set
- Determining positive and negative sample pairs
- Training the image processing model based on these pairs
Potential Applications: - Image recognition technology - Object detection systems - Facial recognition software
Problems Solved: - Enhancing the accuracy of image processing models - Improving the performance of machine learning algorithms
Benefits: - Increased efficiency in image processing tasks - Enhanced accuracy in identifying objects within images
Commercial Applications: Title: Advanced Image Processing Model Training Technology Description: This technology can be utilized in various industries such as security, healthcare, and autonomous vehicles for improved image analysis and recognition capabilities.
Prior Art: Researchers can explore existing patents related to image processing, machine learning, and object detection to understand the evolution of this technology.
Frequently Updated Research: Stay updated on advancements in machine learning algorithms, image processing techniques, and object recognition systems to enhance the performance of the model.
Questions about Image Processing Model Training Technology: 1. How does this method improve the accuracy of image processing models? 2. What are the potential challenges in implementing this technology in real-world applications?
Original Abstract Submitted
disclosed is a method for training an image processing model. the method includes acquiring a plurality of original image sets; cropping the plurality of original images in the plurality of original image sets to acquire a training sample set, wherein each of the training samples represents one original image, or a subimage acquired by cropping one original image; determining a plurality of positive sample pairs and a plurality of negative sample pairs from the training sample set, wherein each of the positive sample pairs comprises two training samples acquired based on different said original images in the same original image set, and each of the negative sample pairs comprises two training samples acquired based on the original images in different said original image sets; and training the image processing model based on the plurality of positive sample pairs and the plurality of negative sample pairs.
