CNN Object-Recognition Notebook: Findings
· 2 min read
This post summarises my CNN object-recognition notebook, including the model setup, training results, test prediction and key limitations of using CIFAR-10 for image classification.
This post summarises my CNN object-recognition notebook, including the model setup, training results, test prediction and key limitations of using CIFAR-10 for image classification.
Wall's article made me think about facial recognition less as a model-accuracy problem and more as a deployment problem: what happens when an organisation treats a CNN score as objective evidence? A convolutional neural network can return a probability or similarity score, but it does not produce truth. In a photo app, a wrong match is irritating; in policing, border control, or military use, it can expose someone to surveillance, exclusion, arrest, or harm (Wall, 2019).