Search for dissertations about: "deep learning"
Showing result 6 - 10 of 360 swedish dissertations containing the words deep learning.
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6. Deep learning for news topic identification in limited supervision and unsupervised settings
Abstract : In today's world, following news is crucial for decision-making and staying informed. With the growing volume of daily news, automated processing is essential for timely insights and in aiding individuals and corporations in navigating the complexities of the information society. READ MORE
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7. Supervised and Unsupervised Deep Learning Models for Flood Detection
Abstract : Human civilization has an increasingly powerful influence on the earthsystem. Affected by climate change and land-use change, floods are occurringacross the globe and are expected to increase in the coming years. Currentsituations urge more focus on efficient monitoring of floods and detecting impactedareas. READ MORE
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8. Machine Learning for Wireless Link Adaptation : Supervised and Reinforcement Learning Theory and Algorithms
Abstract : Wireless data communication is a complex phenomenon. Wireless links encounter random, time-varying, channel effects that are challenging to predict and compensate. Hence, to optimally utilize the channel, wireless links adapt the data transmission parameters in real time. READ MORE
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9. Pith location and annual ring detection for modelling of knots and fibre orientation in structural timber : A Deep-Learning-Based Approach
Abstract : Detection of pith, annual rings and knots in relation to timber board cross-sections is relevant for many purposes, such as for modelling of sawn timber and for real-time assessment of strength, stiffness and shape stability of wood materials. However, the methods that are available and implemented in optical scanners today do not always meet customer accuracy and/or speed requirements. READ MORE
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10. Structured Representations for Explainable Deep Learning
Abstract : 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. READ MORE