Essays about: "Djupa ensembler"
Showing result 1 - 5 of 6 essays containing the words Djupa ensembler.
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1. Uncertainty Estimation in Volumetric Image Segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The performance of deep neural networks and estimations of their robustness has been rapidly developed. In contrast, despite the broad usage of deep convolutional neural networks (CNNs)[1] for medical image segmentation, research on their uncertainty estimations is being far less conducted. READ MORE
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2. Deep Ensembles for Self-Training in NLP
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the development of deep learning methods the requirement of having access to large amounts of data has increased. In this study, we have looked at methods for leveraging unlabeled data while only having access to small amounts of labeled data, which is common in real-world scenarios. READ MORE
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3. 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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4. 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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5. 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
