Aug 17, 2021 · An ameliorated deep dense convolutional neural network (BX-Net) was presented to accurately recognize casting defects in X-ray images.
Aug 17, 2021 · An ameliorated deep dense convolutional neural network (BX-Net) was presented to accurately recognize casting defects in X-ray images.
TL;DR: In this article, an ameliorated deep dense convolutional neural network (BX-Net) was presented to accurately recognize casting defects in X-ray images ...
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摘要. Recognizing defects in X-ray images plays an important role in the detection of internal defects in titanium alloy castings.
Apr 25, 2024 · An ameliorated deep dense convolutional neural network for accurate recognition of casting defects in X-ray images. Knowl. Based Syst. 226 ...
An ameliorated deep dense convolutional neural network for accurate recognition of casting defects in X-ray images. Article. Apr 2021; KNOWL-BASED SYST. Bo Wu ...
Yu et al. [6] proposed a deep convolution neural network-based method to detect the casting defect in X-ray images, which is not.
Missing: ameliorated | Show results with:ameliorated
Exploring deep fully convolutional neural networks for surface defect ...
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Jul 16, 2024 · In this paper, we propose a machine learning approach for detecting superficial defects in metal surfaces using point cloud data.
Missing: ameliorated | Show results with:ameliorated
Based on the publicly available weld seam dataset GDX-ray, this paper proposes a complete technique for fault segmentation in X-ray pictures of pressure vessel ...
This paper presents a weakly-supervised Convolutional Neural Network model to recognize defects based on casting X-ray images. These images are divided into two ...
Missing: ameliorated | Show results with:ameliorated