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Wednesday, June 26 • 11:30 - 11:50
Multitask convolutional neural networks: saving GPU time

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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.

avatar for Paulo Eduardo Sampaio

Paulo Eduardo Sampaio

Data science specialist, McKinsey & Company
Paulo is a civil engineer with a MBA and a MSc in statistics and operations research. He's been working with applied machine learning since 2013 and from 2015 onwards he specialised in computer vision applications. He's currently working for McKinsey as a data science specialist in... Read More →

Wednesday June 26, 2019 11:30 - 11:50 GMT-03
Room 8 Av. Rebouças, 3970 - Pinheiros, São Paulo - SP, 05402-600, Brazil