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Hierarchical fusion convolutional neural networks for SAR image segmentation

  • Published:2021-07 Issue: Volume:147 Page:115-123
  • ISSN:0167-8655
  • Container-title:Pattern Recognition Letters
  • language:en
  • Short-container-title:Pattern Recognition Letters

Author:

Jiang Yinyin,Li Ming,Zhang Peng,Tan Xiaofeng,Song Wanying

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference17 articles.

1. Unsupervised SAR image segmentation using high-order conditional random fields model based on product-of-experts;Zhang;Pattern Recognit. Lett.,2016

2. Thorax disease classification with attention guided convolutional neural network;Guan;Pattern Recognit. Lett.,2020

3. Fast cascade face detection with pyramid network;Zeng;Pattern Recognit. Lett.,2019

4. Combining CNN streams of RGB-D and skeletal data for human activity recognition;Khaire;Pattern Recognit. Lett.,2018

5. ImageNet classification with deep convolutional neural networks;Krizhevsky;Adv. Neural Inf. Process. Syst.,2012

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1. Breaking Visual Barriers: Advanced Neural Networks in Image Layering;2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS);2024-03-08

2. A Multi-decision Fusion Strategy for PolSAR Image Classification;Proceedings of the 2024 7th International Conference on Data Storage and Data Engineering;2024-02-27

3. SAR image classification using deep features and neighborhood heterogeneity confidence refined spatial constraints;International Journal of Remote Sensing;2024-02-14

4. HDTFF-Net: Hierarchical Deep Texture Features Fusion Network for High-Resolution Remote Sensing Scene Classification;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023

5. MASANet: Multi-Angle Self-Attention Network for Semantic Segmentation of Remote Sensing Images;Tehnicki vjesnik - Technical Gazette;2022-10-15
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