☆ 4.7 Article

Multistage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2022)

ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery

Rui Li et al.

Summary: Semantic segmentation of remotely sensed imagery is crucial in various applications, such as environmental protection and precision agriculture. However, current deep learning algorithms often come with high computational demand, hindering real-time practical applications. The proposed ABCNet balances computational efficiency and accuracy, outperforming lightweight benchmark methods in segmentation tasks.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2021)

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Article Environmental Sciences

Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network

Rui Li et al.

REMOTE SENSING (2020)

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Article Geography, Physical

ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data

Foivos Diakogiannis et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

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Article Geography, Physical

Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss

Xianwei Zheng et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

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Article Geography, Physical

Identifying and mapping individual plants in a highly diverse high-elevation ecosystem using UAV imagery and deep learning

Ce Zhang et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

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Article Computer Science, Interdisciplinary Applications

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Zaiwang Gu et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)

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Proceedings Paper Computer Science, Artificial Intelligence

Co-occurrent Features in Semantic Segmentation

Hang Zhang et al.

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)

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Multistage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images

相关参考文献

ABCNet: Attentive bilateral contextual network for efficient semantic segmentation of Fine-Resolution remotely sensed imagery

Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network

ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data

Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss

Identifying and mapping individual plants in a highly diverse high-elevation ecosystem using UAV imagery and deep learning

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Co-occurrent Features in Semantic Segmentation

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