Brain-inspired remote sensing interpretation: A comprehensive survey
Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …
Through research on brain science, the intelligence of remote sensing algorithms can be …
Transformers in small object detection: A benchmark and survey of state-of-the-art
Transformers have rapidly gained popularity in computer vision, especially in the field of
object recognition and detection. Upon examining the outcomes of state-of-the-art object …
object recognition and detection. Upon examining the outcomes of state-of-the-art object …
A task-balanced multiscale adaptive fusion network for object detection in remote sensing images
T Gao, Z Liu, J Zhang, G Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Object detection is essential in the interpretation of remote sensing images (RSIs). However,
the blurred background and objects with vast variances are identified as the two main …
the blurred background and objects with vast variances are identified as the two main …
Decoupled feature pyramid learning for multi-scale object detection in low-altitude remote sensing images
Recently, low-altitude remote sensing platforms are widely used for various practical
applications. Object detection is a basic and significant technology, serving them. The scale …
applications. Object detection is a basic and significant technology, serving them. The scale …
Attention-free global multiscale fusion network for remote sensing object detection
Remote sensing object detection (RSOD) encounters challenges in complex backgrounds
and small object detection, which are interconnected and unable to address separately. To …
and small object detection, which are interconnected and unable to address separately. To …
Structured adversarial self-supervised learning for robust object detection in remote sensing images
Object detection plays a crucial role in scene understanding and has extensive practical
applications. In the field of remote sensing object detection, both detection accuracy and …
applications. In the field of remote sensing object detection, both detection accuracy and …
ST-Trans: Spatial-Temporal Transformer for Infrared Small Target Detection in Sequential Images
X Tong, Z Zuo, S Su, J Wei, X Sun… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The detection of small infrared targets with low signal-to-noise ratio (SNR) and low contrast
in high-noise backgrounds is challenging due to the lack of spatial features of the targets …
in high-noise backgrounds is challenging due to the lack of spatial features of the targets …
GAB-Net: A Robust Detector for Remote Sensing Object Detection under Dramatic Sacle Variation and Complex Backgrounds
Detecting objects in remote sensing images (RSIs), characterized by dramatic scale
variation and complex backgrounds, has always been a challenging problem. These …
variation and complex backgrounds, has always been a challenging problem. These …
Cross-modal Local Calibration and Global Context Modeling Network for RGB-Infrared Remote Sensing Object Detection
J Xie, J Nie, B Ding, M Yu, J Cao - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
RGB–infrared object detection in remote-sensing images is crucial for achieving around-
clock surveillance of unmanned aerial vehicles. RGB–infrared remote-sensing object …
clock surveillance of unmanned aerial vehicles. RGB–infrared remote-sensing object …
Adaptive receptive field enhancement network based on attention mechanism for detecting the small target in the aerial image
J Wang, X Li, L Zhou, J Chen, Z He… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
To address the problem of insufficient semantic feature information caused by small objects
in aerial images, an adaptive receptive field enhancement network based on attention …
in aerial images, an adaptive receptive field enhancement network based on attention …