Essays about: "katastrofal glömska"
Found 4 essays containing the words katastrofal glömska.
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1. A Comparison of CNN and Transformer in Continual Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Within the realm of computer vision tasks, Convolutional Neural Networks (CNN) and Transformers represent two predominant methodologies, often subject to extensive comparative analyses elucidating their respective merits and demerits. This thesis embarks on an exploration of these two models within the framework of continual learning, with a specific focus on their propensities for resisting catastrophic forgetting. READ MORE
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2. Integrating Telecommunications-Specific Language Models into a Trouble Report Retrieval Approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the development of large telecommunications systems, it is imperative to identify, report, analyze and, thereafter, resolve both software and hardware faults. This resolution process often relies on written trouble reports (TRs), that contain information about the observed fault and, after analysis, information about why the fault occurred and the decision to resolve the fault. READ MORE
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3. Continual Learning and Biomedical Image Data : Attempting to sequentially learn medical imaging datasets using continual learning approaches
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : While deep learning has proved to be useful in a large variety of tasks, a limitation remains of needing all classes and samples to be present at the training stage in supervised problems. This is a major issue in the field of biomedical imaging since keeping samples in the training sets consistently is often a liability. READ MORE
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4. Alternative Solution to Catastrophical Forgetting on FewShot Instance Segmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Video instance segmentation is a rapidly-growing research area within the computer vision field. Models for segmentation require data already annotated, which can be a daunting task when starting from scratch. Although there are some publicly available datasets for image instance segmentation, they are limited to the application they target. READ MORE
