Nvidia corporation (20240096074). IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS simplified abstract
Contents
- 1 IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS
Organization Name
Inventor(s)
Brian Okorn of Pittsburgh PA (US)
Arsalan Mousavian of Seattle WA (US)
Lucas Manuelli of Seattle WA (US)
IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240096074 titled 'IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS
Simplified Explanation
The patent application abstract describes apparatuses, systems, and techniques for identifying objects using neural networks and descriptors of object segments.
- Neural networks are utilized to identify objects based on descriptors of object segments.
- The technology involves the use of one or more descriptors to identify one or more objects.
- The system can accurately identify objects through the analysis of segments using neural networks.
Potential Applications
This technology could be applied in various fields such as:
- Object recognition in computer vision systems.
- Autonomous vehicles for object detection.
- Robotics for object manipulation and interaction.
Problems Solved
The technology addresses the following issues:
- Efficient and accurate object identification.
- Automation of object recognition tasks.
- Improved object segmentation and classification.
Benefits
The benefits of this technology include:
- Enhanced object identification capabilities.
- Increased efficiency in object recognition processes.
- Potential for improved decision-making in various applications.
Potential Commercial Applications
This technology has potential commercial applications in:
- Security systems for object detection.
- Manufacturing processes for quality control.
- Retail for inventory management and product recognition.
Possible Prior Art
One possible prior art for this technology could be:
- Object recognition systems using traditional image processing techniques.
Unanswered Questions
How does this technology compare to existing object recognition systems?
The article does not provide a direct comparison with other object recognition systems in terms of accuracy, efficiency, or performance.
What are the limitations of using neural networks for object identification?
The article does not discuss any potential drawbacks or limitations of utilizing neural networks for object identification tasks.
Original Abstract Submitted
apparatuses, systems, and techniques are presented to identify one or more objects. in at least one embodiment, one or more neural networks can be used to identify one or more objects based, at least in part, on one or more descriptors of one or more segments of the one or more objects.
