Hands-On Convolutional Neural Networks with TensorFlow

Datasets

In this section, we will discuss the most important and famous recent datasets used in image classification. This is necessary, because it is likely that any perusal into Computer Vision will overlap with them (including in this book!). Before the arrival of convolutional neural networks, the two main datasets used in image classification competitions by the research community were the Caltech and PASCAL datasets.

The Caltech dataset was established by California Institute of Technology and was released in two versions. Caltech-101 was published in 2003 with 101 categories of about 40 to 800 images per category, and Caltech-256 in 2007 with 256 object categories, containing a total of 30607 images. The images were collected from ...