Essays about: "ReLU"
Showing result 1 - 5 of 20 essays containing the word ReLU.
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1. Developing a highly accurate, locally interpretable neural network for medical image analysis
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Background Machine learning techniques, such as convolutional networks, have shown promise in medical image analysis, including the detection of pediatric pneumonia. However, the interpretability of these models is often lacking, compromising their trustworthiness and acceptance in medical applications. READ MORE
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2. Correlation between Surface and Tumour Motion in Lung Cancer - including Deep Learning Perspectives
University essay from Lunds universitet/SjukhusfysikerutbildningenAbstract : Purpose: The purpose of this master thesis was to retrospectively investigate correlation between surface and tumour motion in lung cancer patients, alongside deep learning applications of the results. Additional correlations such as age, tumour volume and anatomical placement of the tumour were also investigated. READ MORE
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3. Exploring Normalizing Flow Modifications for Improved Model Expressivity
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Normalizing flows represent a class of generative models that exhibit a number of attractive properties, but do not always achieve state-of-the-art performance when it comes to perceived naturalness of generated samples. To improve the quality of generated samples, this thesis examines methods to enhance the expressivity of discrete-time normalizing flow models and thus their ability to capture different aspects of the data. READ MORE
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4. Representation and Efficient Computation of Sparse Matrix for Neural Networks in Customized Hardware
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Deep Neural Networks are widely applied to various kinds of fields nowadays. However, hundreds of thousands of neurons in each layer result in intensive memory storage requirement and a massive number of operations, making it difficult to employ deep neural networks on mobile devices where the hardware resources are limited. READ MORE
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5. Uncertainty quantification for neural network predictions
University essay from Umeå universitet/StatistikAbstract : Since their inception, machine learning methods have proven useful, and their usability continues to grow as new methods are introduced. However, as these methods are used for decision-making in most fields, such as weather forecasting,medicine, and stock market prediction, their reliability must be appropriately evaluated before the models are deployed. READ MORE
