Logo detection and brand visibility analytics

Logo detection and brand visibility analytics

Monitoring brand visibility is an important business problem. We describe our solution for logo detection and visibility analytics with deep learning.

Using deep learning for Single Image Super Resolution

Using deep learning for Single Image Super Resolution

We apply three different deep learning models to reproduce state-of-the-art results in single image super resolution.

Fall 2017 release – launching Neptune 2.1 today!

We’re thrilled today to announce the latest version of Neptune: Machine Learning Lab. This release will allow data scientists using Neptune to take some giant steps forward. Here we take a quick look at each of them.

Solving Atari games with Distributed Reinforcement Learning

Solving Atari games with Distributed Reinforcement Learning

We present the result of research conducted at deepsense.ai, that focuses on distributing a reinforcement learning algorithm to train on a large CPU cluster

Crime forecasting – ‘Minority Report’ realized

Crime forecasting – ‘Minority Report’ realized

Everybody who watched ‘Minority Report’ daydreams about crime forecasting in the real world. We have good news: machine learning algorithms can do that!

Human log loss for image classification

Human log loss for image classification

Deep learning vs human perception: creating a log loss benchmark for industrial & medical image classification problems (e.g. cancer screening).

How to create a product recognition solution

How to create a product recognition solution

In this post we present how to approach product recognition through the example of our solution for the iMaterialist challenge announced by CVPR and Google.

Running distributed TensorFlow on Slurm clusters

Running distributed TensorFlow on Slurm clusters

In this post we show a way to run machine learning experiments with distributed TensorFlow on Slurm clusters. A simple CIFAR-10 example is also included.

Machine learning application in automated reasoning

Despite recent advances in deep learning, the way mathematics is done today is still much the same as it was 100 years ago. Isn’t it time for a change?

Region of interest pooling in TensorFlow – example

In the previous post we explained what region of interest pooling (RoI pooling for short) is. In this one, we present an example of applying RoI pooling in TensorFlow. We base it on our custom RoI pooling TensorFlow operation. We also use Neptune as a support in our experiment performance tracking.