Master GAN: Multiple Attention is all you Need: A Multiple Attention Guided Super Resolution Network for Dems

Author:

Mohammed Azhan1,Kashif Mohammad2,Zama Md Haider2,Ansari Mohammed Abbas2,Ali Saquib2

Affiliation:

1. GalaxEye Space,Bengaluru,India

2. Jamia Millia Islamia,Faculty of Engineering and Technology,Dept. of Computer Engineering,New Delhi,India

Publisher

IEEE

Reference17 articles.

1. Rectifier nonlinearities improve neural network acoustic models;maas,2013

2. Gaussian error linear units (gelus);hendrycks,2016

3. Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

4. Cbam: Convolutional block attention module;woo,2018

5. Attention is all you need;vaswani,2017

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. TFSR: Terrain Factor Super Resolution;2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS);2024-04-12

2. LIE-DSM: Leveraging Single Remote Sensing Imagery to Enhance Digital Surface Model Resolution;IEEE Transactions on Geoscience and Remote Sensing;2024

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