End-to-end airplane detection using transfer learning in remote sensing images
Z Chen, T Zhang, C Ouyang - Remote Sensing, 2018 - mdpi.com
Airplane detection in remote sensing images remains a challenging problem due to the
complexity of backgrounds. In recent years, with the development of deep learning, object …
complexity of backgrounds. In recent years, with the development of deep learning, object …
Hash-based deep learning approach for remote sensing satellite imagery detection
Ship detection plays a crucial role in marine security in remote sensing imagery. This paper
discusses about a deep learning approach to detect the ships from satellite imagery. The …
discusses about a deep learning approach to detect the ships from satellite imagery. The …
[書籍][B] Satellite image analysis: clustering and classification
The satellite imaging system allows easy and effective remote collection of large amounts of
information about the objects of interest from even inaccessible areas for a long time …
information about the objects of interest from even inaccessible areas for a long time …
[PDF][PDF] Automatic target detection in satellite images using deep learning
Automatic target detection in satellite images is a challenging problem due to the varying
size, orientation and background of the target object. The traditionally engineered features …
size, orientation and background of the target object. The traditionally engineered features …
Object detection using convolutional neural networks in a coarse-to-fine manner
X Li, S Wang - IEEE Geoscience and Remote Sensing Letters, 2017 - ieeexplore.ieee.org
Object detection in remote sensing images has long been studied, but it remains
challenging due to the diversity of objects and the complexity of backgrounds. In this letter …
challenging due to the diversity of objects and the complexity of backgrounds. In this letter …
Learning from GPS trajectories of floating car for CNN-based urban road extraction with high-resolution satellite imagery
Deep learning has achieved great success in recent years, among which the convolutional
neural network (CNN) method is outstanding in image segmentation and image recognition …
neural network (CNN) method is outstanding in image segmentation and image recognition …
Aircraft detection in satellite imagery using deep learning-based object detectors
Over the recent years, object detection in satellite imagery has become a crucial task in
remote sensing applications. Specifically, the detection of aircraft is critical for military …
remote sensing applications. Specifically, the detection of aircraft is critical for military …
A hierarchical object detection method in large-scale optical remote sensing satellite imagery using saliency detection and CNN
Z Song, H Sui, L Hua - International Journal of Remote Sensing, 2021 - Taylor & Francis
Detecting geospatial objects, especially small, time-sensitive targets such as airplanes and
ships in cluttered scenes, is a substantial challenge in large-scale, high-resolution optical …
ships in cluttered scenes, is a substantial challenge in large-scale, high-resolution optical …
An aircraft detection framework based on reinforcement learning and convolutional neural networks in remote sensing images
Y Li, K Fu, H Sun, X Sun - Remote sensing, 2018 - mdpi.com
Aircraft detection has attracted increasing attention in the field of remote sensing image
analysis. Complex background, illumination change and variations of aircraft kind and size …
analysis. Complex background, illumination change and variations of aircraft kind and size …
A novel bottleneck residual and self-attention fusion-assisted architecture for land use recognition in remote sensing images
The massive yearly population growth is causing hazards to spread swiftly around the world
and have a detrimental impact on both human life and the world economy. By ensuring early …
and have a detrimental impact on both human life and the world economy. By ensuring early …