The previous TensorFlow article showed you how to write convolutions from scratch in Numpy. Now it’s time to discuss pooling, a downscaling operation that usually follows a convolutional layer. You want to know a secret? It’s not rocket science to implement from scratch. After reading, you’ll know what pooling and strides are... Read more

Editor’s Note: Jennifer is a speaker for ODSC East 2022. Be sure to check out her talk, “Creating a Benchmark for a Large-Scale Image Captioning Pipeline,” to learn more about computer vision deep learning there! Computer vision has an essential role in solving some of the most challenging problems across... Read more

Writing neural network model architectures from scratch involves a lot of guesswork. How many layers? How many nodes per layer? What activation function to use? Regularization? You won’t run out of questions any time soon. Transfer learning takes a different approach. Instead of starting from scratch, you take an existing... Read more

Artificial intelligence (AI) is only as good as the data you give it. That’s a foundational rule for applying any kind of data analytics effectively, yet it remains a challenge in many cases. It’s particularly challenging with computer vision, thanks to JPEG compression defects. Compression issues lead to poor-quality images... Read more

Here, you will find a brief explanation of computer vision, some cases we are experiencing in real life, and some of the existent techniques in data annotation supporting the advance of computer vision. I want to highlight upfront that I’m not approaching any computer vision algorithms in this post. My... Read more

The three authors are speaking at ODSC APAC 2021. Be sure to check out their talk, “Stitching Open Source Components Together to Build an End to End Computer Vision Platform for Your Enterprise,” there! Imagine a scenario where you just got into a meeting with your senior leadership team. They... Read more

When building computer vision solutions, the emphasis is usually on the modeling side and on leveraging the latest algorithm. While the model is important, in my experience I have found that an even more important component to delivering a successful solution is to build and maintain a suitable dataset via... Read more

Companies like eBay and Amazon store millions of images of products; each image contains a wealth of information that can be leveraged to help consumers find the right product or advertise similar products. With the accessibility and effectiveness of computer vision models, namely convolutional neural networks, the high volume of... Read more

So you’re thinking of starting a computer vision program, but you’ve realized now that the logistics are overwhelming. What framework do you use? What infrastructure? Do you go with an out of the box solution or take the time to build your own? Cloud GPU or on-premise? What’s your infrastructure?... Read more

This talk by Ali Vanderveld provides you with a guide for data science leaders and managers who are thinking about starting a computer vision program. It will help you think through a set of sequential questions that you’re likely to encounter along the way: [Related Article: 4 Steps to Start... Read more