Canon kabushiki kaisha (20240296669). IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM simplified abstract
IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM
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IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240296669 titled 'IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM
Simplified Explanation: The patent application describes a method of generating attribute score maps for regions of an input image using a connected layer feature from a hierarchical neural network. These attribute score maps are then integrated to produce a recognition result for a specific target.
- Hierarchical neural network processes input image
- Connected layer feature connects outputs of multiple layers
- Attribute score maps generated for each region of the image
- Recognition result for target produced by integrating attribute score maps
Key Features and Innovation:
- Utilizes hierarchical neural network for image processing
- Generates attribute score maps for image regions
- Integrates attribute score maps for recognition results
- Connected layer feature enhances feature extraction
Potential Applications:
- Image recognition systems
- Object detection in images
- Facial recognition technology
- Medical image analysis
- Autonomous vehicles for scene understanding
Problems Solved:
- Efficient attribute mapping in images
- Improved recognition accuracy
- Enhanced feature extraction
- Streamlined image processing
- Better integration of attribute information
Benefits:
- Accurate recognition results
- Enhanced image analysis capabilities
- Improved performance in various applications
- Streamlined image processing workflows
- Better understanding of image attributes
Commercial Applications: Title: Advanced Image Recognition Technology for Various Industries Potential commercial uses:
- Security and surveillance systems
- Medical imaging devices
- Autonomous vehicles and drones
- Retail analytics for customer behavior analysis
- Quality control in manufacturing processes
Prior Art: Prior art related to this technology may include research on hierarchical neural networks, image recognition systems, and feature extraction methods in neural networks.
Frequently Updated Research: Stay updated on advancements in hierarchical neural networks, image processing techniques, and attribute mapping in image recognition systems.
Questions about Image Recognition Technology: 1. How does the connected layer feature improve attribute mapping in image recognition? 2. What are the potential limitations of integrating attribute score maps for recognition results?
Original Abstract Submitted
a connected layer feature is generated by connecting outputs of a plurality of layers of a hierarchical neural network obtained by processing an input image using the hierarchical neural network. an attribute score map representing an attribute of each region of the input image is generated for each attribute using the connected layer feature. a recognition result for a recognition target is generated and output by integrating the generated attribute score maps for respective attributes.
