Essays about: "neurala faltningsnätverk"
Showing result 1 - 5 of 28 essays containing the words neurala faltningsnätverk.
-
1. Deep Neural Networks as SurrogateModels for Fuel Performance Codes
University essay from Uppsala universitet/Tillämpad kärnfysikAbstract : The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. READ MORE
-
2. Unsupervised Domain Adaptation for Regressive Annotation : Using Domain-Adversarial Training on Eye Image Data for Pupil Detection
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Machine learning has seen a rapid progress the last couple of decades, with more and more powerful neural network models continuously being presented. These neural networks require large amounts of data to train them. READ MORE
-
3. A study of the biological sex in the classification of Alzheimer’s disease using a convolutional neural network
University essay from KTH/DatavetenskapAbstract : This report investigates whether Alzheimer’s MRI scans could be classified more accurately using deep learning if the biological sex was considered. The data used in the study were female and male Alzheimer’s Disease (AD) and Cognitive Normal (CN) MRI scans. The data was divided into a training and test set. READ MORE
-
4. Identifying Melanoma Using Transfer Learning and Convolutional Neural Networks : An investigation of skin disease pre-training
University essay from KTH/DatavetenskapAbstract : Melanoma, the deadliest form of skin cancer, has become an increasingly common and pressing health issue. Early detection and treatment can be life-saving, but also poses a challenge. A possible solution presents itself in Convolutional Neural Networks (CNNs). READ MORE
-
5. Incorporating Metadata Into the Active Learning Cycle for 2D Object Detection
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the past years, Deep Convolutional Neural Networks have proven to be very useful for 2D Object Detection in many applications. These types of networks require large amounts of labeled data, which can be increasingly costly for companies deploying these detectors in practice if the data quality is lacking. READ MORE
