Classification of remote sensing images using EfficientNet-B3 CNN model with attention
Scene classification is a highly useful task in Remote Sensing (RS) applications. Many
efforts have been made to improve the accuracy of RS scene classification. Scene …
efforts have been made to improve the accuracy of RS scene classification. Scene …
Deep feature aggregation framework driven by graph convolutional network for scene classification in remote sensing
K Xu, H Huang, P Deng, Y Li - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
Scene classification of high spatial resolution (HSR) images can provide data support for
many practical applications, such as land planning and utilization, and it has been a crucial …
many practical applications, such as land planning and utilization, and it has been a crucial …
Combing triple-part features of convolutional neural networks for scene classification in remote sensing
H Huang, K Xu - Remote Sensing, 2019 - mdpi.com
High spatial resolution remote sensing (HSRRS) images contain complex geometrical
structures and spatial patterns, and thus HSRRS scene classification has become a …
structures and spatial patterns, and thus HSRRS scene classification has become a …
Weighted spatial pyramid matching collaborative representation for remote-sensing-image scene classification
At present, nonparametric subspace classifiers, such as collaborative representation-based
classification (CRC) and sparse representation-based classification (SRC), are widely used …
classification (CRC) and sparse representation-based classification (SRC), are widely used …
RETRACTED: Attention-Based Deep Feature Fusion for the Scene Classification of High-Resolution Remote Sensing Images
R Zhu, L Yan, N Mo, Y Liu - Remote Sensing, 2019 - mdpi.com
Scene classification of high-resolution remote sensing images (HRRSI) is one of the most
important means of land-cover classification. Deep learning techniques, especially the …
important means of land-cover classification. Deep learning techniques, especially the …
基于CNN-GCN 双流网络的高分辨率遥感影像场景分类.
邓培芳， 徐科杰， 黄鸿 - Journal of Remote Sensing, 2021 - search.ebscohost.com
高分辨率遥感影像具有复杂的几何结构和空间布局, 传统的卷积神经网络的方法仅能提取场景
图像中的全局特征, 忽略了上下文的关系, 导致特征的表达能力受限, 制约了分类精度提高 …
图像中的全局特征, 忽略了上下文的关系, 导致特征的表达能力受限, 制约了分类精度提高 …
Remote sensing scene classification and explanation using RSSCNet and LIME
Classification is needed in disaster investigation, traffic control, and land-use resource
management. How to quickly and accurately classify such remote sensing imagery has …
management. How to quickly and accurately classify such remote sensing imagery has …
Deep open-set domain adaptation for cross-scene classification based on adversarial learning and Pareto ranking
Most of the existing domain adaptation (DA) methods proposed in the context of remote
sensing imagery assume the presence of the same land-cover classes in the source and …
sensing imagery assume the presence of the same land-cover classes in the source and …
Aggregated deep fisher feature for VHR remote sensing scene classification
With the development of very high resolution satellite image acquisition technology, remote
sensing scene classification has become an important and challenging task. In this article …
sensing scene classification has become an important and challenging task. In this article …
Extracting feature fusion and co-saliency clusters using transfer learning techniques for improving remote sensing scene classification
To attribute the semantics to land cover, scene classification of very high-resolution (VHR)
imagery comprises many possible applications in diverse domains. Conventional remote …
imagery comprises many possible applications in diverse domains. Conventional remote …