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Filtering by: Creator Mark Harmon Type Work Keyword Basketball Trajectory Keyword Stock Prediction Subject Engineering Sciences and Applied Mathematics

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1. Methods for Images, Time Series, and Activation Functions with Deep Neural Networks

Description:: In this work, we explore the utility of the three main types of neural networks: feed forward, convolutional, and recurrent. While using these networks, we develop a new way to model multiagent trajectory data, explore the use of multiple activation functions for neurons at each layer of a neural network,...
Keyword:: Stock Prediction, Deep Learning, Basketball Trajectory, Activation Functions, and Machine Learning
Subject:: Engineering Sciences and Applied Mathematics
Creator:: Mark Harmon
Owner:: Scholarly Digital Publishing
Date Uploaded:: 10/14/2019
Date Modified:: 10/14/2019
Date Created:: 2018-01-01
Resource Type:: Dissertation

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1. Methods for Images, Time Series, and Activation Functions with Deep Neural Networks

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1. Methods for Images, Time Series, and Activation Functions with Deep Neural Networks