FADNet : Greenhouse Identification with Fusion Attention Mechanism and Deformable Convolution

Liu, Jun and Xu, Xiaolong and Bilal, Muhammad and Jiang, Jielin (2024) FADNet : Greenhouse Identification with Fusion Attention Mechanism and Deformable Convolution. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17. 7170 - 7178. ISSN 1939-1404

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Abstract

With the development of agricultural modernization, strengthening the supervision of agricultural production activities plays a crucial role in social security management and economic development. However, the current monitoring of greenhouse usage and planning in agricultural production lacks effective regulation. Existing technological approaches involve the analysis and monitoring of agricultural activities using machine learning and simple neural networks, but their detection accuracy is limited. In this paper, we present a novel deep learning model called FADNet, which fusion attention mechanism and variable convolution techniques. FADNet utilizes remotely sensed images obtained from satellite sensors as input for training. It employs variable convolution and feature pyramid networks to achieve accurate segmentation of small-scale greenhouse targets. Spatial attention mechanism is employed to address the interference caused by similar features in urban areas for greenhouse identification. Additionally, data augmentation techniques are utilized to address the scarcity of greenhouse datasets and the disparity in the distribution of positive and negative samples, thereby enhancing the reliability of the dataset. FADNet achieves greenhouse segmentation by performing pixel-level classification on the images. Extensive experiments have demonstrated that FADNet performs exceptionally well in greenhouse segmentation tasks.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1900/1903
Subjects:
?? attention mechanismconvolutiondecodingdeep learningdeformable convolutionfeature extractiongreen productsgreenhouse identificationimage segmentationremote satellite sensingtask analysistrainingcomputers in earth sciencesatmospheric science ??
ID Code:
216797
Deposited By:
Deposited On:
22 Mar 2024 10:10
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 01:02