Essays about: "Upptäckt av träning"
Showing result 1 - 5 of 9 essays containing the words Upptäckt av träning.
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1. Software Fault Detection in Telecom Networks using Bi-level Federated Graph Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The increasing complexity of telecom networks, induced by the recent development of 5G, is a challenge for detecting faults in the telecom network. In addition to the structural complexity of telecommunication systems, data accessibility has become an issue both in terms of privacy and access cost. READ MORE
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2. Neuromorphic Medical Image Analysis at the Edge : On-Edge training with the Akida Brainchip
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Computed Tomography (CT) scans play a crucial role in medical imaging, allowing neuroscientists to identify intracranial pathologies such as haemorrhages and malignant tumours in the brain. This thesis explores the potential of deep learning models as an aid in intracranial pathology detection through medical imaging. READ MORE
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3. Exploring the Feasibility of Exercise Detection on the Exxentric kBox Platform
University essay from KTH/Medicinteknik och hälsosystemAbstract : Flywheel training is an increasingly popular training method that aids in the recovery process and promotes strength development while reducing the risk of re-injury. Additionally, automatic exercise classification offers athletes the convenience of effortlessly monitoring and tracking their training progress, enabling them to maintain consistency and achieve their fitness goals effectively. READ MORE
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4. Deep Learning Models for Detecting Breast Cancer : A Comparative Study
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Breast cancer is the second leading cause of death for women worldwide. As early detection is vital, new methods for facilitating accurate diagnosis are continuously being developed. READ MORE
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5. Optimizing the Performance of Text Classification Models by Improving the Isotropy of the Embeddings using a Joint Loss Function
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recent studies show that the spatial distribution of the sentence representations generated from pre-trained language models is highly anisotropic, meaning that the representations are not uniformly distributed among the directions of the embedding space. Thus, the expressiveness of the embedding space is limited, as the embeddings are less distinguishable and less diverse. READ MORE