18661525. IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM simplified abstract (CANON KABUSHIKI KAISHA)
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 18661525 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 in a hierarchical neural network, which are then integrated to produce a recognition result for a recognition target.
Key Features and Innovation:
- Generation of attribute score maps for regions of an input image.
- Integration of attribute score maps to produce a recognition result.
- Utilization of a connected layer feature in a hierarchical neural network.
Potential Applications: This technology can be applied in various fields such as image recognition, object detection, and pattern analysis.
Problems Solved: This technology addresses the need for accurate attribute recognition in complex images and enhances the efficiency of image processing tasks.
Benefits:
- Improved accuracy in attribute recognition.
- Enhanced performance in image processing tasks.
- Increased efficiency in pattern analysis.
Commercial Applications: Potential commercial applications include automated image tagging systems, surveillance systems, and quality control in manufacturing processes.
Prior Art: Readers can start their search for prior art related to this technology by exploring patents in the field of image processing, neural networks, and computer vision.
Frequently Updated Research: Researchers are constantly exploring advancements in neural network architectures, image processing algorithms, and attribute recognition techniques that could further enhance the capabilities of this technology.
Questions about Attribute Recognition Technology: 1. How does the connected layer feature in a hierarchical neural network contribute to attribute recognition in images? 2. What are the potential limitations of integrating attribute score maps for different attributes in image recognition tasks?
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.
