Essays about: "Deep Ensembles"

Showing result 1 - 5 of 12 essays containing the words Deep Ensembles.

1. 1. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

   University essay from Lunds universitet/Matematik LTH

   Author : Marisa Wodrich; [2024]
   Keywords : Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

   Abstract : 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

3. 2. 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 systemteknik

   Author : Kevin Coleman; [2023]
   Keywords : Radar Emitter Classification; Pulse Descriptor Word; Out of Distribution Detection; Dataset Drift; Uncertainty Estimation; Deep Ensembles; Recurrent Neural Networks; LSTM;

   Abstract : 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

4. 3. Real-time uncertainty estimation for deep learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Árni Dagur Guðmundsson; [2023]
   Keywords : Machine Learning; Deep Learning; Uncertainty Estimation; Evidential Deep Learning; Computer Vision; Maskininlärning; Djupinlärning; Osäkerhetsuppskattning; Evidential Deep Learning; Datorseende; Vélnám; Djúptauganet; Óvissumat; Evidential Deep Learning; Tölvusjón;

   Abstract : Modern deep neural networks do not produce well calibrated estimates of their own uncertainty, unless specific uncertainty estimation techniques are applied. Common uncertainty estimation techniques such as Deep Ensembles and Monte Carlo Dropout necessitate multiple forward pass evaluations for each input sample, making them too slow for real-time use. READ MORE

5. 4. Uncertainty Estimation in Volumetric Image Segmentation

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Donggyun Park; [2023]
   Keywords : Uncertainty Estimation; Uncertainty Quantification UQ ; Volumetric Image Segmentation; 3D U-Net; test-time data augmentation; Deep ensemble;

   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

6. 5. Hybrid Deep Learning Model for Cellular Network Traffic Prediction : Case Study using Telecom Time Series Data, Satellite Imagery, and Weather Data

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Ali Shibli; [2022]
   Keywords : Cellular network traffic; multi-modal; satellite imagery; weather data; LSTM; CNN; time series; Trafic sur les réseaux cellulaires; multimodal; imagerie satellite; données météo; LSTM; CNN; séries temporelles; Förutsägelse av mobilnätstrafik; multimodal modell; satellitbilder; väderdata; LSTM; CNN; tidsseriein;

   Abstract : Cellular network traffic prediction is a critical challenge for communication providers, which is important for use cases such as traffic steering and base station resources management. Traditional prediction methods mostly rely on historical time-series data to predict traffic load, which often fail to model the real world and capture surrounding environment conditions. READ MORE