18451287. METHOD AND APPARATUS WITH OBJECT DETECTOR TRAINING simplified abstract (Samsung Electronics Co., Ltd.)
Contents
- 1 METHOD AND APPARATUS WITH OBJECT DETECTOR TRAINING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS WITH OBJECT DETECTOR TRAINING - 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 Original Abstract Submitted
METHOD AND APPARATUS WITH OBJECT DETECTOR TRAINING
Organization Name
Inventor(s)
Gyusam Chang of Seongnam-si (KR)
METHOD AND APPARATUS WITH OBJECT DETECTOR TRAINING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18451287 titled 'METHOD AND APPARATUS WITH OBJECT DETECTOR TRAINING
Simplified Explanation
The abstract describes a method and apparatus for object detector training, involving obtaining input data from a target object, performing data augmentation, extracting features to a shared embedding space, identifying loss functions, and updating weights based on the loss functions.
- Obtaining input data from a target object
- Performing data augmentation on the input data
- Extracting features to a shared embedding space
- Identifying loss functions based on the extracted features
- Updating weights of the encoder based on the loss functions
Potential Applications
This technology can be applied in various fields such as computer vision, autonomous driving, surveillance systems, and robotics for object detection and recognition tasks.
Problems Solved
This technology helps improve the accuracy and efficiency of object detection systems by training the detectors with augmented data and shared embedding spaces, leading to better feature extraction and loss function identification.
Benefits
The benefits of this technology include enhanced object detection performance, increased robustness to variations in input data, and improved generalization capabilities for different object detection tasks.
Potential Commercial Applications
The potential commercial applications of this technology include developing advanced object detection systems for security, retail, manufacturing, and healthcare industries, as well as for autonomous vehicles and drones.
Possible Prior Art
One possible prior art for this technology could be the use of data augmentation techniques in machine learning and computer vision to improve model performance and generalization capabilities.
Unanswered Questions
How does this technology compare to existing object detection methods?
This article does not provide a direct comparison with existing object detection methods in terms of performance, efficiency, or accuracy.
What are the computational requirements for implementing this technology?
The article does not mention the computational resources needed to implement this method, such as processing power, memory, or training time.
Original Abstract Submitted
A method and apparatus with object detector training is provided. The method includes obtaining first input data and second input data from a target object; obtaining second additional input data by performing data augmentation on the second input data; extracting a first feature to a shared embedding space by inputting the first input data to a first encoder; extracting a second feature to the shared embedding space by inputting the second input data to a second encoder; extracting a second additional feature to the shared embedding space by inputting thesecond additional input data to the second encoder; identifying a first loss function based on the first feature, the second feature, and the second additional feature; identifying a second loss function based on the second feature and the second additional feature; and updating a weight of the second encoder based on the first loss function and the second loss function.
