Sökning: "Self-supervised"
Visar resultat 1 - 5 av 14 avhandlingar innehållade ordet Self-supervised.
1. Self-supervised deep learning and EEG categorization
Sammanfattning : Deep learning has the potential to be used to improve and streamline EEG analysis. At the present, classifiers and supervised learning dominate the field. Supervised learning depends on target labels which most often are created by human experts manually classifying data. LÄS MER
2. Self-supervised Representation Learning for Visual Domains Beyond Natural Scenes
Sammanfattning : This thesis investigates the possibility of efficiently adapting self-supervised representation learning on visual domains beyond natural scenes, e.g., medical imagining and non-RGB sensory images. LÄS MER
3. Structured Representations for Explainable Deep Learning
Sammanfattning : Deep learning has revolutionized scientific research and is being used to take decisions in increasingly complex scenarios. With growing power comes a growing demand for transparency and interpretability. The field of Explainable AI aims to provide explanations for the predictions of AI systems. LÄS MER
4. Geometric Supervision and Deep Structured Models for Image Segmentation
Sammanfattning : The task of semantic segmentation aims at understanding an image at a pixel level. Due to its applicability in many areas, such as autonomous vehicles, robotics and medical surgery assistance, semantic segmentation has become an essential task in image analysis. LÄS MER
5. Semi-supervised learning with self-supervision for closed and open sets
Sammanfattning : Semi-supervised learning (SSL) is a learning framework that enables the use of unlabeled data with labeled data. These methods play a crucial role in reducing the burden of human labeling in training deep learning models. Many methods for SSL learn from unlabeled data through confidence-based pseudo-labeling. LÄS MER