Essays about: "out-of-distribution detection"
Showing result 1 - 5 of 11 essays containing the words out-of-distribution detection.
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1. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging
University essay from Lunds universitet/Matematik LTHAbstract : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. READ MORE
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2. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis
University essay from Lunds universitet/Matematik LTHAbstract : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. READ MORE
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3. Dataset Drift in Radar Warning Receivers : Out-of-Distribution Detection for Radar Emitter Classification using an RNN-based Deep Ensemble
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Changes to the signal environment of a radar warning receiver (RWR) over time through dataset drift can negatively affect a machine learning (ML) model, deployed for radar emitter classification (REC). The training data comes from a simulator at Saab AB, in the form of pulsed radar in a time-series. READ MORE
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4. Detecting Images Outside Training Distribution for Fingerprint Spoof Detection
University essay from Lunds universitet/Matematik LTHAbstract : Artificial neural networks are known to run into issues when given samples that deviate from the training distribution, where the network may confidently provide an incorrect answer. Out-of-distribution detection methods aims to provide a solution to this issue, by detecting data that deviates from the distribution used to train the model. READ MORE
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5. Diffusion models for anomaly detection in digital pathology
University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakultetenAbstract : Challenges within the field of pathology leads to a high workload for pathologists. Machine learning has the ability to assist pathologists in their daily work and has shown good performance in a research setting. READ MORE