The facial image under eyeglasses occlusion can degrade face recognition performance. Inspired by the success of deep convolutional neural networks (DCNN) on super resolution, in this paper, a method based on deep convolutional neural network is developed for automatic eyeglasses removal from frontal facial images. To remove eyeglasses on facial images, the proposed approach applied deep convolution neural networks (end-to-end DCNN) to reconstruct the eyeglasses region. We adopt the deep convolutional neural networks (DCNN) approach is designed and trained to learn the mapping between pairs of face images with or without eyeglasses from a large face database in video surveillance. The extensive experiments show that the proposed algorithm can effectively remove eyeglasses, and also can keep the stability of face recognition under eyeglasses on occlusion.

This chapter investigates advanced localization techniques for unmanned aerial vehicles (UAVs), focusing on the challenges and solutions associated with both indoor and outdoor environments. By examining a range of positioning strategies, including the global positioning system (GPS), visible light communication (VLC), and vision-based methods, this chapter presents a comprehensive overview of the current state and future potential of UAV localization. The integration of various sensors and the strategic use of landmarks as reference points are explored to enhance localization accuracy. Moreover, two pioneering prototypes that are designed to mitigate the limitations identified in current technologies are introduced for case study. A modularization approach for VLC systems and an empirical method for vision-based distance estimation employing multi-scale QR codes. This chapter also highlights the role of sensor fusion and artificial intelligence in improving the precision and efficiency of UAV navigation. Through proof-of-concept experiments utilizing photodiodes (PDs), inertial measurement units (IMUs), and cameras, we demonstrate the practical applicability and effectiveness of the discussed methodologies. Finally, we study the practical applicability and effectiveness of the discussed systems and their experimental results. Our investigations illustrate significant superiority in UAV localization technologies, paving the way for expanded applications across diverse industries and complex operational scenarios.