人工智能
计算机科学
航空影像
无人机
卷积神经网络
深度学习
图像处理
目标检测
计算机视觉
图像(数学)
图像分割
分割
模式识别(心理学)
特征检测(计算机视觉)
遗传学
生物
作者
Xinni Liu,Kamarul Hawari Ghazali,Fang Han,Izzeldin Ibrahim Mohamed
标识
DOI:10.1080/13682199.2023.2174651
摘要
In recent years, deep learning algorithm has been used in many applications mainly in image processing of object detection and classification. The use of image processing techniques is becoming more interesting with the existence of drone technology with the employ of deep learning in aerial view image processing because of the high resolution and heaps of images taken. This paper aims to review neural networks specifically on the aerial view image by drones and to discuss the work principles and classic architectures of convolutional neural networks, its latest research trend and typical models along with target detection in object detection, image classification and semantic segmentation. In addition, this study also provided a specific application in the aerial image. Finally, the limitations of the convolutional network and expected future development trends were also discussed. Based on the findings, the deep learning algorithm was observed to provide high accuracy, it outperformed other generally image processing-based techniques.
科研通智能强力驱动
Strongly Powered by AbleSci AI