3 posts tagged with "Computer Vision"

I used CNN Explainer to follow two images through a small convolutional neural network: an espresso, which matches one of the model's trained classes, and a sunflower, which does not. Comparing them exposed a basic limitation of image classifiers: a model can only choose from the labels and examples represented in its dataset.

My CNN object-recognition notebook covers the model setup, training results, a test prediction and the limitations of using CIFAR-10 for image classification.

Using Yu et al. (2024) as a comparison framework, I consider how conventional machine learning and deep learning could be evaluated for production-line visual inspection, and how their decisions could be explained to the people expected to act on them.