Essays about: "backpropagation algorithms"
Showing result 1 - 5 of 18 essays containing the words backpropagation algorithms.
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1. Estimation of dissolved organic carbon from inland waters using remote sensing data and machine learning
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : This thesis presents the first attempt to estimate Dissolved Organic Carbon (DOC) in inland waters over a large-scale area using satellite data and machine learning (ML) methods. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were tested to retrieve DOC using a filtered version of the recently published open source AquaSat dataset with more than 16 thousand samples across the continental US matched with satellite data from Landsat 5, 7 and 8 missions. READ MORE
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2. Building and Training a Fully Connected Deep Neural Network From Scratch
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Artificial Neural Networks make up the core of mostMachine Learning algorithms. In the past decade Machine learninghave successfully taken on fields such as image recognition,Data analytics and medical technologies. READ MORE
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3. Spiking Reinforcement Learning for Robust Robot Control Under Varying Operating Conditions
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over the last few years, deep reinforcement learning (RL) has gained increasing popularity for its successful application to a variety of complex control and decision-making tasks. As the demand for deep RL algorithms deployed in challenging real-world environments grows, their robustness towards uncertainty, disturbances and perturbations of the environment becomes more and more important. READ MORE
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4. The derivation of first- and second-order backpropagation methods for fully-connected and convolutional neural networks
University essay from Lunds universitet/Matematik LTH; Lunds universitet/MatematikcentrumAbstract : We introduce rigorous theory for deriving first and second order backpropagation methods for Deep Neural Networks (DNN) whilst satisfying existing theory in DNN optimization. We begin by formally defining a neural network with its respective components and state the first and second order chain rule with respect to its partial derivatives. READ MORE
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5. Training Neural Networks with Evolutionary Algorithms for Flash Call Verification
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Evolutionary algorithms have achieved great performance among a wide range of optimization problems. In this degree project, the network optimization problem has been reformulated and solved in an evolved way. A feasible evolutionary framework has been designed and implemented to train neural networks in supervised learning scenarios. READ MORE
