Essays about: "self-supervised learning"
Showing result 6 - 10 of 49 essays containing the words self-supervised learning.
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6. 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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7. Self-supervised representation learning from electrocardiogram data for medical applications
University essay from Lunds universitet/Matematik LTHAbstract : Cardiovascular diseases are the leading cause of death worldwide, increasing yearly. However, many abnormalities in heart cycles can be discovered and treated years before the onset of diseases. But in most societies, regular health checkups are a concept reserved for cars, not humans. READ MORE
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8. Quantification of DNA Microballs Using Image Processing Techniques
University essay from KTH/Industriell bioteknologiAbstract : I detta examensarbete användes olika bildbehandlingstekniker för detektion och kvantifiering av DNA-mikrobollar, mer specifikt rolling circle amplification-produkter, på mikroskopibilder. Avsikten med detta arbete var att hjälpa Countagen AB utforska pipelines för bildbehandling för sin produkt där de analyserar utfallet av genredigeringsförsök på ett billigare och snabbare sätt än dagens konventionella sekvenseringsmetoder. READ MORE
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9. Improving Change Point Detection Using Self-Supervised VAEs : A Study on Distance Metrics and Hyperparameters in Time Series Analysis
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis addresses the optimization of the Variational Autoencoder-based Change Point Detection (VAE-CP) approach in time series analysis, a vital component in data-driven decision making. We evaluate the impact of various distance metrics and hyperparameters on the model’s performance using a systematic exploration and robustness testing on diverse real-world datasets. READ MORE
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10. Applicability of Detection Transformers in Resource-Constrained Environments : Investigating Detection Transformer Performance Under Computational Limitations and Scarcity of Annotated Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Object detection is a fundamental task in computer vision, with significant applications in various domains. However, the reliance on large-scale annotated data and computational resource demands poses challenges in practical implementation. READ MORE
