View source for 18753187. SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM simplified abstract (SONY SEMICONDUCTOR SOLUTIONS CORPORATION)

=SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM=


==Organization Name==

[[:Category:SONY SEMICONDUCTOR SOLUTIONS CORPORATION|SONY SEMICONDUCTOR SOLUTIONS CORPORATION]]


[[Category:SONY SEMICONDUCTOR SOLUTIONS CORPORATION]]

==Inventor(s)==

[[:Category:SEIGO Hanada of KANAGAWA (JP)|SEIGO Hanada of KANAGAWA (JP)]][[Category:SEIGO Hanada of KANAGAWA (JP)]]

[[:Category:SUGURU Kobayashi of KANAGAWA (JP)|SUGURU Kobayashi of KANAGAWA (JP)]][[Category:SUGURU Kobayashi of KANAGAWA (JP)]]

==SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18753187 titled 'SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM

'''Simplified Explanation''': 
The patent application describes a system that uses two deep neural network (DNN) processing units to process image data in two stages, generating results sequentially.

'''Key Features and Innovation''':
* Utilizes a first DNN processing unit in a solid-state image capturing device to execute part of a DNN algorithm on image data.
* The first result generated by the first DNN processing unit is then passed to a second DNN processing unit in an information processing device.
* The second DNN processing unit executes the remaining part of the DNN algorithm to generate a second result.

'''Potential Applications''':
* Image processing and analysis in various industries such as healthcare, security, and automotive.
* Real-time object recognition and classification in surveillance systems.
* Enhanced image quality and feature extraction in digital cameras and smartphones.

'''Problems Solved''':
* Streamlines the processing of complex DNN algorithms for image analysis.
* Improves efficiency and accuracy in image recognition tasks.
* Enables seamless integration of DNN technology in image capturing devices.

'''Benefits''':
* Faster and more accurate image processing.
* Enhanced capabilities for object detection and classification.
* Potential for improved image quality and feature extraction.

'''Commercial Applications''':
The technology could be applied in industries such as:
* Healthcare for medical imaging analysis.
* Security for surveillance systems.
* Automotive for driver assistance systems.

'''Questions about the Technology''':
1. How does the use of two DNN processing units improve image processing efficiency?
2. What are the potential limitations of this system in real-world applications?

'''Frequently Updated Research''':
Stay updated on advancements in DNN algorithms and image processing techniques to enhance the system's performance and capabilities.


==Original Abstract Submitted==

A solid-state image capturing system () includes a solid-state image capturing device () and an information processing device (). The solid-state image capturing device () includes a first DNN processing unit () that executes, on image data, a part of a DNN algorithm by a first DNN to generate a first result. The information processing device () includes a second DNN processing unit () that executes, on the first result acquired from the solid-state image capturing device, remaining of the DNN algorithm by a second DNN to generate a second result.



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[[Category:G06V10/764]]
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[[Category:H04N25/771]]
[[Category:CPC_G06N3/063]]