Lithology Identification of Improved Model based on DeepLabv3 + Deep Convolutional Neural Network

Aiming at the complexity of outcrop lithology identification, an improved outcrop lithology identification algorithm based on DeepLabv3 + is proposed. We use the Xception network replaced by the MobileNetV2 module to enhance the ability to extract lithologic features and make the model more lightwei...

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Veröffentlicht in:	2024 International Conference on New Trends in Computational Intelligence (NTCI) S. 533 - 537
Hauptverfasser:	Wang, Ju, Yin, Senlin, Hu, Zhangming, Bai, Kai
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 18.10.2024
Schlagworte:	Accuracy Attention mechanism Attention mechanisms Classification algorithms Complexity theory Computational intelligence Computational modeling Convolutional neural networks Feature extraction lightweight model lithology identification Semantic segmentation
Online-Zugang:	Volltext
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