[HTML][HTML] Effect of attention mechanism in deep learning-based remote sensing image processing: A systematic literature review

S Ghaffarian, J Valente, M Van Der Voort… - Remote Sensing, 2021‏ - mdpi.com
Machine learning, particularly deep learning (DL), has become a central and state-of-the-art
method for several computer vision applications and remote sensing (RS) image …

Intelligent image semantic segmentation: a review through deep learning techniques for remote sensing image analysis

B Jiang, X An, S Xu, Z Chen - Journal of the Indian society of remote …, 2023‏ - Springer
Image semantic segmentation is an important part of fundamental in image interpretation
and computer vision. With the development of convolutional neural network technology …

LANet: Local attention embedding to improve the semantic segmentation of remote sensing images

L Ding, H Tang, L Bruzzone - IEEE Transactions on Geoscience …, 2020‏ - ieeexplore.ieee.org
The trade-off between feature representation power and spatial localization accuracy is
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …

High-resolution remote sensing image captioning based on structured attention

R Zhao, Z Shi, Z Zou - IEEE Transactions on Geoscience and …, 2021‏ - ieeexplore.ieee.org
Automatically generating language descriptions of remote sensing images has become an
emerging research hot spot in the remote sensing field. Attention-based captioning, as a …

A deep learning method for optimizing semantic segmentation accuracy of remote sensing images based on improved UNet

X Wang, Z Hu, S Shi, M Hou, L Xu, X Zhang - Scientific reports, 2023‏ - nature.com
Semantic segmentation of remote sensing imagery (RSI) is critical in many domains due to
the diverse landscapes and different sizes of geo-objects that RSI contains, making …

Dual-path feature aware network for remote sensing image semantic segmentation

J Geng, S Song, W Jiang - … on Circuits and Systems for Video …, 2023‏ - ieeexplore.ieee.org
Semantic segmentation is a significant task for remote sensing interpretation, which takes
advantage of contextual semantic information to classify each pixel into a specific category …

[HTML][HTML] Encoding contextual information by interlacing transformer and convolution for remote sensing imagery semantic segmentation

X Li, F Xu, R **a, T Li, Z Chen, X Wang, Z Xu, X Lyu - Remote Sensing, 2022‏ - mdpi.com
Contextual information plays a pivotal role in the semantic segmentation of remote sensing
imagery (RSI) due to the imbalanced distributions and ubiquitous intra-class variants. The …

Attention guided contextual feature fusion network for salient object detection

J Zhang, Y Shi, Q Zhang, L Cui, Y Chen, Y Yi - Image and Vision …, 2022‏ - Elsevier
In recent years, the Convolutional Neural Network (CNN) has been widely used in various
visual tasks because of its powerful feature extraction ability. Salient object detection …

High-order semantic decoupling network for remote sensing image semantic segmentation

C Zheng, J Nie, Z Wang, N Song… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Low-order features based on convolution kernel are easy to be distorted when encountering
dramatic view angle transformation and atmospheric scattering in remote sensing (RS) …

Real-Time Semantic Segmentation: A brief survey and comparative study in remote sensing

C Broni-Bediako, J **a, N Yokoya - IEEE Geoscience and …, 2023‏ - ieeexplore.ieee.org
Real-time semantic segmentation of remote sensing imagery is a challenging task that
requires a tradeoff between effectiveness and efficiency. It has many applications, including …