An example of an image classification problem is to identify a photograph of an animal as a "dog" or "cat" or "monkey." The two most common approaches for image classification are to use a standard ...

When something does zero-shot image classification, that means it’s able to make judgments about the contents of an image without the user needing to train the system beforehand on what to look ...

When evaluating an image classification model, Shared Interest compares the model-generated saliency data and the human-generated ground-truth data for the same image to see how well they align.

Researchers at Auburn University trained a neural network to fool Google's best image-recognition system, Inception, by rotating objects in space to novel positions. The lesson is that today's AI ...

Creating a custom image classification model is challenging, but the existence of neural network libraries like Keras has made it doable. Here's how, with many code samples and a full project download ...