17581550. IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS simplified abstract (NVIDIA Corporation)
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 17581550 titled 'IDENTIFYING OBJECTS USING NEURAL NETWORK-GENERATED DESCRIPTORS
Simplified Explanation
The patent application abstract describes the use of neural networks to identify objects based on descriptors of segments of the objects.
- Neural networks are utilized to identify objects by analyzing descriptors of object segments.
- The technology can be used to accurately identify one or more objects.
- The system may involve multiple neural networks working together to identify objects effectively.
Potential Applications
This technology could be applied in various fields such as:
- Object recognition in autonomous vehicles
- Security and surveillance systems
- Medical imaging for identifying specific anatomical structures
Problems Solved
The technology helps in:
- Improving object identification accuracy
- Enhancing efficiency in object recognition tasks
- Reducing human error in object identification processes
Benefits
The benefits of this technology include:
- Faster and more accurate object identification
- Enhanced automation in various industries
- Improved overall system performance
Potential Commercial Applications
The potential commercial applications of this technology include:
- Integration into smart cameras for enhanced object recognition
- Implementation in robotics for object manipulation tasks
- Inclusion in quality control systems for product inspection
Possible Prior Art
One possible prior art for this technology could be the use of traditional computer vision techniques for object identification. However, the use of neural networks for this purpose represents a significant advancement in accuracy and efficiency.
Unanswered Questions
How does the system handle complex objects with multiple segments?
The article does not provide details on how the technology deals with objects that have intricate structures or multiple segments.
What is the computational complexity of the neural network system?
The abstract does not mention the computational resources required for running the neural networks and their impact on real-time applications.
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.
