Company Filing History:
Years Active: 2022
Title: Ningning Qu: Innovator in Dim and Small Object Detection
Introduction
Ningning Qu is a prominent inventor based in Beijing, China. He has made significant contributions to the field of object detection, particularly through his innovative methods that enhance detection accuracy. His work is particularly relevant in the context of video satellite data, where precision is crucial.
Latest Patents
Ningning Qu holds a patent titled "Method for dim and small object detection based on discriminant feature of video satellite data." This method utilizes a discriminant feature to improve the detection accuracy of dim and small objects. The approach incorporates a symmetric semantic segmentation model and an autoencoder model to extract the discriminant feature of an object. Additionally, a top-down adjustment mechanism is employed to fuse image features with the discriminant feature. An attention mechanism is also utilized to enhance the background, increasing the contrast between the object and its surroundings. Furthermore, a multi-scale semantic analysis strategy is introduced, using a pyramid model to effectively extract dim and small objects from video satellite data. Ningning Qu has 1 patent to his name.
Career Highlights
Ningning Qu is affiliated with the Beijing University of Civil Engineering and Architecture, where he continues to advance his research and innovation in the field. His academic background and professional experience have positioned him as a key figure in the development of advanced detection methods.
Collaborations
Ningning Qu has collaborated with notable colleagues, including Jingguo Lv and Yifei Cao. Their combined expertise contributes to the ongoing research and development in object detection technologies.
Conclusion
Ningning Qu's innovative work in the detection of dim and small objects through video satellite data showcases his commitment to advancing technology in this critical area. His contributions are paving the way for more accurate and efficient detection methods in various applications.