Essays about: "faltningsnätverk"
Showing result 36 - 40 of 77 essays containing the word faltningsnätverk.
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36. Eye Tracking Using a Smartphone Camera and Deep Learning
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Tracking eye movements has been a central part in understanding attention and visual processing in the mind. Studying how the eyes move and what they fixate on during specific moments has been considered by some to offer a direct way to measure spatial attention. READ MORE
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37. One-shot learning through generalized representations with neural networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Despite the rapid progress in the field of machine learning and artificial neural networks, many hurdles yet remain before machines can match human capabilities. One such hurdle is the copious amount of data required for these learning machines to reach adequate performance. READ MORE
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38. Detecting quantum speedup for random walks with artificial neural networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Random walks on graphs are an essential base for crucial algorithms for solving problems, like the boolean satisfiability problem. A speedup of random walks could improve these algorithms. The quantum version of the random walk, quantum walk, is faster than random walks in specific cases, e.g. READ MORE
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39. One-Shot Neural Architecture Search for Deep Multi-Task Learning in Computer Vision
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this work, a neural architecture search algorithm for multi-task learning is proposed. Given any dataset and tasks group, the method aims to find the optimal way of sharing layers among tasks in convolutional neural networks. READ MORE
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40. Automatic Generation of Patient-specific Gamma Knife Treatment Plans for Vestibular Schwannoma Patients
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this thesis a new fully automatic process for radiotherapy treatment planning with the Leksell Gamma Knife is implemented and evaluated: First, a machine learning algorithm is trained to predict the desired dose distribution, then a convex optimization problem is solved to find the optimal Gamma Knife configuration using the prediction as the optimization objective. The method is evaluated using Bayesian linear regression, Gaussian processes and convolutional neural networks for the prediction. READ MORE
