Essays about: "Ensembler"
Showing result 6 - 10 of 14 essays containing the word Ensembler.
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6. Uncertainty Estimation for Deep Learning-based LPI Radar Classification : A Comparative Study of Bayesian Neural Networks and Deep Ensembles
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Deep Neural Networks (DNNs) have shown promising results in classifying known Low-probability-of-intercept (LPI) radar signals in noisy environments. However, regular DNNs produce low-quality confidence and uncertainty estimates, making them unreliable, which inhibit deployment in real-world settings. READ MORE
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7. Boosting CNN Performance in Digital Pathology Using Colour Normalisation and Ensembling
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Researchers within digital pathology are endeavouringto develop machine-learning tools to support dentists whenmaking a diagnosis. The purpose of this study was to investigatehow applying colour normalisation (CN) algorithms on an oral,histopathological dataset would impact both machine-learningmodels and ensembles of models when classifying cell types. READ MORE
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8. Ensembles of Single Image Super-Resolution Generative Adversarial Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Generative Adversarial Networks have been used to obtain state-of-the-art results for low-level computer vision tasks like single image super-resolution, however, they are notoriously difficult to train due to the instability related to the competing minimax framework. Additionally, traditional ensembling mechanisms cannot be effectively applied with these types of networks due to the resources they require at inference time and the complexity of their architectures. READ MORE
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9. Comparing Non-Bayesian Uncertainty Evaluation Methods in Chromosome Classification by Using Deep Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Chromosome classification is one of the essential tasks in karyotyping to diagnose genetic abnormalities like some types of cancers and Down syndrome. Deep convolutional neural networks have been widely used in this task, and the accuracy of classification models is exceptionally critical to such sensitive medical diagnoses. READ MORE
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10. Neural Networks and Uncertainty Estimation for Financial Asset Predictions
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the capability of modeling complex non-linear mappings, neural networks have obtained state-of-the-art performance on various tasks. However, traditional neural networks are prone to overfitting as they tend to be overconfident on unseen, noisy and incorrectly labeled data. Neither do they produce meaningful representations of uncertainty. READ MORE
