The R-CNN deep learning model Above: R-CNN architecture. The Region-based Convolutional Neural Network (R-CNN) was proposed by AI researchers at the University of California, Berkley, in 2014.

The R-CNN deep learning model R-CNN architecture. The Region-based Convolutional Neural Network (R-CNN) was proposed by AI researchers at the University of California, Berkley, in 2014.

Depending on the deep learning architecture, data size, and task at hand, we sometimes require 1 GPU, and sometimes, several of them, a decision data scientist needs to make based on known ...

“Deep compression is useful in real-world neural networks and can save a great deal in terms of the number of computations and the bandwidth demands.” Below is the Aristotle architecture, which is ...