Sony semiconductor solutions corporation (20240346299). SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM simplified abstract
Contents
- 1 SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 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
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Questions about the Technology
- 1.11 Original Abstract Submitted
SOLID-STATE IMAGE CAPTURING SYSTEM, SOLID STATE IMAGE CAPTURING DEVICE, INFORMATION PROCESSING DEVICE, IMAGE PROCESSING METHOD, INFORMATION PROCESSING METHOD, AND PROGRAM
Organization Name
sony semiconductor solutions corporation
Inventor(s)
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 20240346299 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 to generate a final result.
- The system includes a solid-state image capturing device with a first DNN processing unit that executes part of a DNN algorithm to produce an initial result.
- An information processing device then uses a second DNN processing unit to complete the DNN algorithm on the initial result and generate a final result.
Key Features and Innovation
- Utilizes two DNN processing units to process image data in stages.
- Improves the efficiency and accuracy of image processing.
- Allows for complex DNN algorithms to be executed in a distributed manner.
Potential Applications
The technology can be applied in various fields such as:
- Surveillance systems
- Autonomous vehicles
- Medical imaging
- Quality control in manufacturing
Problems Solved
- Enhances the speed and accuracy of image processing.
- Enables the execution of complex DNN algorithms on image data.
- Facilitates distributed processing of image data.
Benefits
- Improved efficiency in image processing tasks.
- Enhanced accuracy in generating results.
- Enables the use of advanced DNN algorithms in real-time applications.
Commercial Applications
- The technology can be used in industries such as security, healthcare, automotive, and manufacturing for efficient image processing tasks.
Questions about the Technology
What are the potential limitations of using two DNN processing units in image processing?
Using two DNN processing units may increase the complexity of the system and require additional computational resources. It could also introduce latency issues in real-time applications.
How does the system handle large volumes of image data efficiently?
The system likely employs optimization techniques and parallel processing to handle large volumes of image data efficiently.
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.
