18029022. METHOD AND APPARATUS FOR CODING FEATURE MAP BASED ON DEEP LEARNING IN MULTITASKING SYSTEM FOR MACHINE VISION simplified abstract (Hyundai Motor Company)
Contents
- 1 METHOD AND APPARATUS FOR CODING FEATURE MAP BASED ON DEEP LEARNING IN MULTITASKING SYSTEM FOR MACHINE VISION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS FOR CODING FEATURE MAP BASED ON DEEP LEARNING IN MULTITASKING SYSTEM FOR MACHINE VISION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Original Abstract Submitted
METHOD AND APPARATUS FOR CODING FEATURE MAP BASED ON DEEP LEARNING IN MULTITASKING SYSTEM FOR MACHINE VISION
Organization Name
Inventor(s)
Seung Wook Park of Yongin-si (KR)
Wha Pyeong Lim of Hwaseong-si (KR)
METHOD AND APPARATUS FOR CODING FEATURE MAP BASED ON DEEP LEARNING IN MULTITASKING SYSTEM FOR MACHINE VISION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18029022 titled 'METHOD AND APPARATUS FOR CODING FEATURE MAP BASED ON DEEP LEARNING IN MULTITASKING SYSTEM FOR MACHINE VISION
Simplified Explanation
The patent application describes a VCM coding apparatus and method for generating and compressing a common feature map related to multiple tasks in a machine vision system.
- The VCM coding apparatus utilizes deep learning-based techniques for feature map coding in a multitasking system.
- It can generate and compress task-specific feature maps as needed for improved performance.
- The technology aims to ensure acceptable performance for both machine vision and human vision.
Potential Applications
- Machine vision systems
- Video processing applications
- Surveillance systems
Problems Solved
- Efficient generation and compression of feature maps for multitasking systems
- Improved performance in machine vision tasks
- Adaptability to different tasks without sacrificing performance
Benefits
- Enhanced performance in machine vision applications
- Flexibility to generate task-specific feature maps
- Improved efficiency in processing large amounts of visual data
Original Abstract Submitted
A VCM coding apparatus and a VCM coding method, related to a deep learning-based feature map coding apparatus in a multitasking system for machine vision, are provided for performing default procedures of generating and compressing a common feature map related to multiple tasks implied by an original video. The VCM coding apparatus and the VCM coding method can further generate and compress a task-specific feature map whenever needed for higher performance than obtainable with the common feature map to ensure relatively acceptable performance for both machine vision and human vision.
