Grigory Serebryakov (Xperience.AI)
In Machine Learning, we always want to get insights into data: like getting familiar with the training samples or better understanding the label distribution. To do that, we visualize the
In the previous post, we learned how to classify arbitrarily sized images and visualized the response map of the network. In Figure 1, notice that the head of the camel
In this post, we will learn how to perform image classification on arbitrary sized images without using the computationally expensive sliding window approach. This post is written for people who
