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Video Outpainting using Conditional Generative Adverarial Networks
(2021)
Recent advancements in machine learning and neural networks have pushed the boundaries of what computers can achieve. Generative adversarial networks are a specific type of neural network that have proved wildly successful ...
Evaluating GAM-Like Neural Network Architectures for Interpretable Machine Learning
(2019-05)
In many machine learning applications, interpretability is of the utmost importance. Artificial intelligence is proliferating, but before you entrust your finances, your well-being, or even your life to a machine, you’d ...
Automated Detection of Bird Roosts Using NEXRAD Radar Data and Convolutional Neural Networks
(2017-12-15)
NEXRAD radars have proven to be an effective tool for detecting bird roosts for several species or birds, however manually locating these roosts in radar images is a time consuming process. We introduce a Convolutional ...
Promoting Speciation Through Variable Dominance in Genetic Algorithms
(2020-05)
Genetic algorithms are a class of search algorithms that have been around since the 1970s. Despite their age, genetic algorithms still see a great deal of use in various applications and so many efforts have gone into ...
Real-Time Gesture Recognition with Mini Drones
(2018-12-14)
Drones are being used worldwide to perform many functions - medical deliveries, video recording, and surveying to name a few. Their growing presence is paralleled by the growing world of Machine Learning (ML). This thesis ...
Deep Learning for Weak Target Detection in Range-Doppler Data
(2022-05)
A consistent issue for detectors in radar systems is how to correctly distinguish target signals from random noise. This is especially true for weak targets with low signal-to-noise ratios (SNRs). Traditional target detection ...