Deep learning-based object detection techniques for remote sensing images: A survey
Z Li, Y Wang, N Zhang, Y Zhang, Z Zhao, D Xu, G Ben… - Remote Sensing, 2022 - mdpi.com
Object detection in remote sensing images (RSIs) requires the locating and classifying of
objects of interest, which is a hot topic in RSI analysis research. With the development of …
objects of interest, which is a hot topic in RSI analysis research. With the development of …
[HTML][HTML] Cost-efficient information extraction from massive remote sensing data: When weakly supervised deep learning meets remote sensing big data
With many platforms and sensors continuously observing the earth surface, the large
amount of remote sensing data presents a big data challenge. While remote sensing data …
amount of remote sensing data presents a big data challenge. While remote sensing data …
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 …
Federated learning for computer vision
Computer Vision (CV) is playing a significant role in transforming society by utilizing
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
Weakly supervised object detection for remote sensing images: A survey
The rapid development of remote sensing technologies and the availability of many satellite
and aerial sensors have boosted the collection of large volumes of high-resolution images …
and aerial sensors have boosted the collection of large volumes of high-resolution images …
High-Quality Instance Mining and Dynamic Label Assignment for Weakly Supervised Object Detection in Remote Sensing Images
Weakly supervised object detection (WSOD) in remote sensing images (RSIs) has attracted
more and more attention because its training merely relies on image-level category labels …
more and more attention because its training merely relies on image-level category labels …
FPN-GAN: multi-class small object detection in remote sensing images
Despite the recent dramatic advances in object detection, detecting a small object in general
and in remote sensing images is still a challenging problem. One main reason for this is the …
and in remote sensing images is still a challenging problem. One main reason for this is the …
Energy-efficient adaptive sensing scheduling in wireless sensor networks using Fibonacci tree optimization algorithm
L Wu, H Cai - Sensors, 2021 - mdpi.com
Wireless sensor networks are appealing, largely because they do not need wired
infrastructure, but it is precisely this feature that renders them energy-constrained. The duty …
infrastructure, but it is precisely this feature that renders them energy-constrained. The duty …
Weakly supervised object detection from remote sensing images via self-attention distillation and instance-aware mining
P Yang, S Zhou, L Wang, G Yang - Multimedia Tools and Applications, 2024 - Springer
Weakly supervised object detection (WSOD) is an effective method to train object detectors
using only image-level category labels, and has been concerned in the field of remote …
using only image-level category labels, and has been concerned in the field of remote …
Object detection in aerial remote sensing images using bidirectional enhancement FPN and attention module with data augmentation
P Yang, D Yu, G Yang - Multimedia Tools and Applications, 2024 - Springer
Object detection for aerial remote sensing images is a foundation task in earth observation
community. However, various challenges still exist in this field, including the varied …
community. However, various challenges still exist in this field, including the varied …