Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Siamese neural network"”.
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Modeling image-to-image confusions in memory
… they find those pairs. Finally, we train a Siamese neural network to predict confusions between pairs of images. By studying the mechanisms behind the failures of memory, we hope to increase our understanding of memory as a whole and move closer to a computational model of memory.
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Deep learning based semantic textual similarity for applications in translation technology
… word embeddings. We also propose a novel Siamese neural network based on efficient recurrent neural network units. We empirically evaluate various unsupervised and supervised STS methods, including these newly proposed methods in three different English STS datasets, two non- English …
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Image registration and bias evaluation for a COVID-19 pulmonary X-ray severity (PXS) score prediction algorithm
… intra-rater variability. One study has used a Siamese neural network to predict numerical COVID-19 pulmonary disease severity scores [19], but because CXRs from the same patient tend to have differences in positioning and acquisition unrelated to disease progression, image registration can be …
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Machine learning based speech quality prediction
… deep learning architectures, such as CNNs, LSTM networks, and Transformer/self-attention networks were combined and compared. It was found that a network with CNN, Self-Attention, and a proposed attention-pooling delivers the best single-ended speech quality predictions on the considered dataset. …
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Neural Network Supervision: Notes on Loss Functions, Labels and Confidence Estimation
… a number of enhancements to the standard neural network training paradigm. First, we show that carefully designed parameter update rules may replace the need for a loss function and its gradient. We introduce a parameter update rule that generalises the standard cross-entropy gradient, and …
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Using Siamese neural networks to identify individual animals
… image in the pair. Mask-Regional Convolution Neural Networks (Mask - RCNN) [He et al., 2017] are used for the object detection and instance segmentation which answers (1). This is a modern deep learning approach which has been used for tasks such as identifying breast cancer tumors [Chiao et …
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Computational methods and machine learning for crosslinking mass spectrometry data analysis
… can be accurately predicted through deep neural networks. Fifth, the ability to predict not only hSAX, but also strong cation exchange (SCX) and reversed-phase retention times indeed proves to be a valuable addition for the identification of crosslinked peptides. Siamese neural network …
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FCoder: A real-time large-scale bottleneck detection mechanism with neural network and transfer learning
Detecting shared bottlenecks among network flows is crucial in TCP Multipath to ensure TCP fairness and other applications related to cross-flow congestion control. The problem of whether two flows share a bottleneck has been well investigated in previous work, but a large-scale bottleneck …