18537975. INSPECTION DEVICE AND METHOD OF INSPECTION USING THE SAME simplified abstract (Samsung Display Co., LTD.)
Contents
INSPECTION DEVICE AND METHOD OF INSPECTION USING THE SAME
Organization Name
Inventor(s)
DOOHYOUNG Lee of Yongin-si (KR)
KUHWAN Chung of Yongin-si (KR)
JOO DONG Yun of Yongin-si (KR)
SANGHYUNG Lim of Yongin-si (KR)
INSPECTION DEVICE AND METHOD OF INSPECTION USING THE SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 18537975 titled 'INSPECTION DEVICE AND METHOD OF INSPECTION USING THE SAME
The inspection device described in the patent application includes an image output unit, a storage unit, and a neural network processing unit.
- The image output unit generates an inspection image for an inspection target containing an oxide semiconductor.
- The storage unit stores multiple reference images and reference data indicating oxygen vacancy distribution, created through an artificial neural network.
- The neural network processing unit compares the reference images with the inspection image, selects a corresponding reference image, and outputs an oxygen vacancy distribution image based on the selected reference data.
Potential Applications:
- Quality control in semiconductor manufacturing processes.
- Defect detection in oxide semiconductors.
- Research and development in neural network-based image processing technologies.
Problems Solved:
- Efficient identification of oxygen vacancy distribution in oxide semiconductors.
- Enhanced accuracy in comparing inspection images with reference data.
- Streamlined inspection processes in semiconductor production.
Benefits:
- Improved quality control in semiconductor manufacturing.
- Increased efficiency in defect detection.
- Enhanced accuracy in analyzing oxygen vacancy distribution.
Commercial Applications:
- Semiconductor manufacturing companies can integrate this technology into their quality control processes to ensure the reliability of their products.
- Research institutions focusing on semiconductor materials can utilize this device for in-depth analysis of oxide semiconductors.
Questions about the technology: 1. How does the neural network processing unit determine the selection reference image corresponding to the inspection image? 2. What are the specific parameters used in the artificial neural network to generate the reference data for oxygen vacancy distribution?
Frequently Updated Research: Researchers are constantly exploring new applications for artificial neural networks in image processing, which could lead to further advancements in semiconductor inspection technologies.
Original Abstract Submitted
Provided is an inspection device including an image output unit configured to output an inspection image for an inspection target including an oxide semiconductor, a storage unit configured to store a plurality of reference images and a plurality of reference data indicating oxygen vacancy distribution, which are generated through an artificial neural network, and a neural network processing unit configured to compare the reference images with the inspection image and select a selection reference image corresponding to the inspection image, and output an oxygen vacancy distribution image based on selection reference data corresponding to the selection reference image.
