Transformer with Transfer CNN for Remote-Sensing-Image Object Detection

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 4; p. 984
• Main Authors: Li, Qingyun, Chen, Yushi, Zeng, Ying
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2022
• Subjects: Algorithms; Artificial neural networks; Coders; convolutional neural network (CNN); Data augmentation; data collection; Datasets; Decoders; Feature extraction; Methods; Neural networks; object detection; Object recognition; Proposals; Remote sensing; remote-sensing images; Sensors; Training; transfer learning; Transformer; Transformers

Object detection in remote-sensing images (RSIs) is always a vibrant research topic in the remote-sensing community. Recently, deep-convolutional-neural-network (CNN)-based methods, including region-CNN-based and You-Only-Look-Once-based methods, have become the de-facto standard for RSI object dete...