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object detection
Building a Custom Mask RCNN Model with TensorFlow Object Detection
Doing cool things with data! You can now build a custom Mask RCNN model using TensorFlow Object Detection Library! Mask RCNN is an instance segmentation model that can identify pixel-by-pixel location of any object. This article is the second part of my popular post where I explain the basics of Mask RCNN model... Read more
Overview of the YOLO Object Detection Algorithm
Let’s review the YOLO (You Only Look Once) real-time object detection algorithm, which is one of the most effective object detection algorithms that also encompasses many of the most innovative ideas coming out of the computer vision research community. Object detection is a critical capability of autonomous vehicle technology. It’s... Read more
Using TensorFlow Object Detection to do Pixel Wise Classification
In the past, I have used TensorFlow Object Detection API to implement object detection with the output being bounding boxes around different objects of interest in the image. For more please look at my article. TensorFlow recently added new functionality and now we can extend the API to determine pixel by... Read more
Using Object Detection for a Smarter Retail Checkout Experience
I have been playing around with the Tensorflow Object Detection API and have been amazed by how powerful these models are. I want to share the performance of the API for some practical use cases. The first use case is a smarter retail checkout experience. This is a hot field right now... Read more
Analyze a Soccer Game Using Tensorflow Object Detection and OpenCV
Introduction The world cup season is here and off to an interesting start. Whoever thought the reigning champions Germany would be eliminated in the group stage 🙁 For the data scientist within you, lets use this opportunity to do some analysis on soccer clips. With the use of deep learning and... Read more
Image Detection as a Service
Across our two brands, Badoo and Bumble, we have over 500 million registered users worldwide uploading millions of photos a day to our platform. These images provide us with a rich data set from which we derive a wealth of insights. User Profile Information Within our data science team, we... Read more
Discovering 135 Nights of Sleep with Data, Anomaly Detection, and Time Series
In this article, I look at data from 135 nights of sleep and use anomaly detection and time series data to understand the results. Three things are certain in life: death, taxes, and sleeping. Here, we’ll talk about the latest. Every night*, us humans, after a long day of roaming... Read more
Multi-Task Learning Objectives for Natural Language Processing
In a previous blog post, I discussed how multi-task learning (MTL) can be used to improve the performance of a model by leveraging a related task. Multi-task learning consists of two main components: a) The architecture used for learning and b) the auxiliary task(s) that are trained jointly. Both facets still... Read more
Neural Magic Launches High-Performance Inference Engine and Tool Suite for CPUs
Run computer vision models at lower cost with a suite of new tools that simplify model performance. Today, Neural Magic is announcing the release of its Inference Engine software, the NM Model Repo, and our ML Tooling. Now, data science teams can run computer vision models in production on commodity... Read more
Processing Images Through Segmentation Algorithms
Image segmentation is considered one of the most vital progressions of image processing. It is a technique of dividing an image into different parts, called segments. It is primarily beneficial for applications like object recognition or image compression because, for these types of applications, it is expensive to process the... Read more