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Research on Deep Learning-based Object Detection and Its Derivative Key Technologies

Submission Deadline: 31 March 2025 View: 279 Submit to Special Issue

Guest Editors

Dr. Guanqiu Qi, State University of New York at Buffalo State, USA

Dr. Zhiqin Zhu, Chongqing University of Posts and Telecommunications, China

Dr. Zhihao Zhou, Chongqing University of Posts and Telecommunications, China

Prof. Yinong Chen, Arizona State University, USA

Summary

In digital image processing, the detection of specific objects and the resulting tasks of object classification, recognition, and segmentation are extremely important. These related technologies have now been widely applied in various fields such as autonomous driving, aerospace, medical diagnosis, remote sensing image analysis, and more. They have achieved numerous breakthrough applications, transforming the path of human societal progress. In recent years, with the rapid evolution of deep learning technology, object detection-related technologies have further developed at a fast pace. They have been extensively applied to the identification and detection of various signs and objects in autonomous driving, autonomous flight and delivery by drones, tumor segmentation and lesion diagnosis in medical imaging, and the interpretation and key object recognition in remote sensing imagery, all of which have advanced the mode of social operation.


Keywords

Project topics include, but are not limited to, the following:
Image Object Detection
Object Detection for Autopilot
Image Segmentation for Autopilot
Object Detection for Remote Sensing
Image Segmentation for Remote Sensing
Medical Image lesion Detection
Medical Image Segmentation
Image Object Classification
Object Classification for Autopilot
Human Machine Interface
Flexible sensing technology
Flexible display
Data security and privacy considerations in digital health solutions

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