Essays about: "självövervakad inlärning"
Showing result 1 - 5 of 11 essays containing the words självövervakad inlärning.
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1. Self-learning for 3D segmentation of medical images from single and few-slice annotation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Training deep-learning networks to segment a particular region of interest (ROI) in 3D medical acquisitions (also called volumes) usually requires annotating a lot of data upstream because of the predominant fully supervised nature of the existing stateof-the-art models. To alleviate this annotation burden for medical experts and the associated cost, leveraging self-learning models, whose strength lies in their ability to be trained with unlabeled data, is a natural and straightforward approach. READ MORE
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2. Self-supervised pre-training of an attention-based model for 3D medical image segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Accurate segmentation of anatomical structures is crucial for radiation therapy in cancer treatment. Deep learning methods have been demonstrated effective for segmentation of 3D medical images, establishing the current standard. However, they require large amounts of labelled data and suffer from reduced performance on domain shift. READ MORE
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3. Feature extraction from MEG data using self-supervised learning : Investigating contrastive representation learning methods to f ind informative representations
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Modern day society is vastly complex, with information and data constantly being posted, shared, and collected everywhere. There is often an abundance of massive amounts of unlabeled data that can not be leveraged in a supervised machine learning context. READ MORE
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4. XAI-assisted Radio Resource Management: Feature selection and SHAP enhancement
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the fast development of radio technologies, wireless systems have become more convoluted. This complexity, accompanied by an increase of the number of connections, is translated into a need for more parameters to analyse and decisions to take at each instant. READ MORE
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5. Analysis of Brain Signals from Patients with Parkinson’s Disease using Self-Supervised Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Parkinson’s disease (PD) is one of the most common neurodegenerative brain disorders, commonly diagnosed and monitored via clinical examinations, which can be imprecise and lead to a delayed or inaccurate diagnosis. Therefore, recent research has focused on finding biomarkers by analyzing brain networks’ neural activity to find abnormalities associated with PD pathology. READ MORE
