Redesigning U-Net with dense connection and attention module for satellite based cloud detection
Abstract
In this paper, we present an upgraded U-Net technique for satellite-based cloud detection, with additional features, such as, more relevant spatial information, improvement in gradient propagation, feature reuse and controlling the network parameters using growth rate by adding dense connections. Furthermore, incorporation of attention module helps to learn strong inter-spatial and inter-channel relationships of feature maps by adding a few trainable parameters to the network. The two attention blocks namely position attention module (PAM) and channel attention module (CAM) focus on important parts of the image by neglecting the redundant information. The experimental results prove that the put forward technique with dense and attention modules could detect cloud with an accuracy of 95.69%.
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PDFDOI: http://doi.org/10.11591/ijai.v11.i2.pp699-708
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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).