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Keywords: convolutional neural networkClose
Proc. ASME. IMECE2021, Volume 2A: Advanced Manufacturing, V02AT02A010, November 1–5, 2021
Paper No: IMECE2021-70500
... structural and cyclic loading applications. Understanding the mechanisms of defect formation and identifying the defects play an important role in improving the product lifecycle. While convolutional neural network (CNN) has already been demonstrated to be an effective deep learning tool for automated...
Proc. ASME. IMECE2021, Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging, V012T12A013, November 1–5, 2021
Paper No: IMECE2021-73114
... the coefficients of a multi-parameter stress field equation by minimizing the convergence error iteratively in a non-linear least squares sense. This is a multi-stage, semi-automatic approach. In this paper, the power of convolutional neural networks (CNN) that are well suited for recognizing complex spatial...
Proc. ASME. IMECE2019, Volume 3: Biomedical and Biotechnology Engineering, V003T04A023, November 11–14, 2019
Paper No: IMECE2019-11125
...INFLUENCE OF INPUT IMAGE CONFIGURATIONS ON OUTPUT OF A CONVOLUTIONAL NEURAL NETWORK TO DETECT CEREBRAL ANEURYSMS Kazuhiro Watanabe Institute of Fluid Science, Tohoku University, Sendai, Miyagi, Japan Graduate School of Biomedical Engineering, Tohoku University, Sendai, Miyagi, Japan Hitomi Anzai...