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Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery
With the rapid development of deep learning, many deep learning-based approaches have
made great achievements in object detection tasks. It is generally known that deep learning …
made great achievements in object detection tasks. It is generally known that deep learning …
RingMo: A remote sensing foundation model with masked image modeling
Deep learning approaches have contributed to the rapid development of remote sensing
(RS) image interpretation. The most widely used training paradigm is to use ImageNet …
(RS) image interpretation. The most widely used training paradigm is to use ImageNet …
[HTML][HTML] YOLO-SE: Improved YOLOv8 for remote sensing object detection and recognition
T Wu, Y Dong - Applied Sciences, 2023 - mdpi.com
Object detection remains a pivotal aspect of remote sensing image analysis, and recent
strides in Earth observation technology coupled with convolutional neural networks (CNNs) …
strides in Earth observation technology coupled with convolutional neural networks (CNNs) …
Tools, techniques, datasets and application areas for object detection in an image: a review
J Kaur, W Singh - Multimedia Tools and Applications, 2022 - Springer
Object detection is one of the most fundamental and challenging tasks to locate objects in
images and videos. Over the past, it has gained much attention to do more research on …
images and videos. Over the past, it has gained much attention to do more research on …
An anchor-free detection method for ship targets in high-resolution SAR images
Z Sun, M Dai, X Leng, Y Lei, B **-Ji/publication/356123149_A_New_Spatial-Oriented_Object_Detection_Framework_for_Remote_Sensing_Images/links/61ce5567b6b5667157b8c0d7/A-New-Spatial-Oriented-Object-Detection-Framework-for-Remote-Sensing-Images.pdf" data-clk="hl=th&sa=T&oi=gga&ct=gga&cd=7&d=5845461691817459977&ei=3Fe_Z_myOY-w6rQPjtMM" data-clk-atid="CQHvKHBAH1EJ" target="_blank">[PDF] researchgate.net
A new spatial-oriented object detection framework for remote sensing images
Although the orientation and scale properties of the objects in remote sensing images have
been widely considered in the modern deep learning-based object detection methods, the …
been widely considered in the modern deep learning-based object detection methods, the …
Remote sensing object detection meets deep learning: A metareview of challenges and advances
Remote sensing object detection (RSOD), one of the most fundamental and challenging
tasks in the remote sensing field, has received long-standing attention. In recent years, deep …
tasks in the remote sensing field, has received long-standing attention. In recent years, deep …
Yolo-hr: Improved yolov5 for object detection in high-resolution optical remote sensing images
D Wan, R Lu, S Wang, S Shen, T Xu, X Lang - Remote Sensing, 2023 - mdpi.com
Object detection is essential to the interpretation of optical remote sensing images and can
serve as a foundation for research into additional visual tasks that utilize remote sensing …
serve as a foundation for research into additional visual tasks that utilize remote sensing …