• <xmp id="om0om">
  • <table id="om0om"><noscript id="om0om"></noscript></table>
  • After clicking “Watch Now” you will be prompted to login or join.


    Click “Watch Now” to login or join the NVIDIA Developer Program.


    Weakly Supervised Training to Achieve 99% Accuracy for Retail Asset Protection

    Bhavesh Patel , Dell EMC | Matt Scott, Malong Technologies

    GTC 2020

    We'll present an efficient way to train deep neural networks on large-scale, weakly-supervised data learned from regular retail customer asset-protection behaviors, without any expert annotation. We'll develop a principled learning strategy by leveraging curriculum learning to effectively handle a massive number of noisy labels and data imbalance. Our new learning curriculum measures the complexity of data using its distribution density in a feature space, and ranks that complexity without supervision. This allows for an efficient implementation of curriculum learning on large-scale retail images, resulting in a high-performance convolutional neural network model, where the negative impact of noisy labels is reduced substantially.

    View More GTC 2020 Content