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- 1Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
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Automated semantic segmentation of NiCrBSi-WC optical microscopy images using convolutional neural networks
Download2022-01-01
Rose, D., Forth, J., Henein, H., Wolfe, T., Qureshi, A.
Convolutional neural networks (CNNs) were used for the semantic segmentation of angular monocrystalline WC from NiCrBSi-WC optical microscopy images. This deep learning approach was able to emulate the laborious task of manual segmentation effectively, with a mean intersection over union (IOU)...
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Extending Differentiable Programming to include Non-differentiable Modules using Differentiable Bypass for Combining Convolutional Neural Networks and Dynamic Programming into an End-to-end Trainable Framework
DownloadSpring 2019
Differentiable Programming is the paradigm where different functions or modules are combined into a unified pipeline with the purpose of applying end-to-end learning or optimization. A natural impediment is the non-differentiability characteristic of many modules. This thesis proposes a new way...