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Deep Learning

Data Science from Concept to Production: A Case Study of Automatic Building Footprint Segmentation

Data Science from Concept to Production: A Case Study of Automatic Building Footprint Segmentation

Using Deep Learning and Computer Vision techniques, aerial imagery can be analyzed to automatically predict or augment structure annotations in both form and area...

Eye Tracking: Activation Functions

Eye Tracking: Activation Functions

While experimenting with multiple architectures, I took the opportunity to step back and consider how I might confine the output of the neural network to be a bit more specific to the GazeCapture of iOS devices.

Eye Tracking Update: Neural Network Architecture and Loss Functions

Eye Tracking Update: Neural Network Architecture and Loss Functions

Background As a part of my graduate studies at Regis University, I have had the opportunity to begin exploring my own project during my Deep Learning class. (Data Source) By using this data set before my practicum (Spring 2019), I hope to not only explore and model some interesting data

GPUs or CPUs for Deep Learning?

GPUs or CPUs for Deep Learning?

Photo [https://www.pexels.com/photo/blur-close-up-computer-device-343239/] by Jordan Harrison [https://www.pexels.com/@jord] from Pexels [https://www.pexels.com/] The repurposing and expansion of GPUs for neural network calculations has revolutionized the possibilities of deep neural network architectures and made large, general-purpose models like Inception and RestNet computationally