Using convolutional neural network to classify bacterial vs fungal keratitis from images

Final project for CS229 (Machine Learning) at Stanford





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Puppy sleep/wake classifier for security camera

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Motivation:   Asleep I wake up at a consistent time every morning to take my puppy out of her play pen / crate and give her breakfast. However, sometimes after late nights of work I prefer to sleep in a little if possible, and sometimes my puppy is not awake at the early hours of the morning. If I can time my alarm to match when my puppy wakes up, I may be able to get some more sleep. Solution:  Using a security camera and a ML model, I can classify whether my puppy is asleep or awake, then send this information to an iPhone app that wakes me up if necessary. Awake Progress:   So far I have completed the data collection and training of the model. In total, I collected and manually labeled 1137 photos using a script that retrieves photos from the security camera. I then trained a CNN (transfer learning using ResNet-50).  These are the bootstrap 95% confidence intervals of key metrics: Accuracy: 0.951 to 0.991 AUROC:  0.988 to 0.9996 F1 Score: 0.934 to 0.988 ...
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