PAPIs Latam 2019

Convolutional neural networks are great for image classification, there's no doubt about it. The problem is: each one you add to your pipeline increase processing time and require more GPU memory, which can get quite costly. We'll discuss how to deal with that by training convolutional neural networks with multiple classifiers sharing the convolutional layers. We'll evaluate the results in a dataset of apparel products, discussing impact in accuracy and on the quality of the embedding.