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Introducing Bounding Box Level Augmentations

18 Mar 2020 • 3 min read

Introducing Bounding Box Level Augmentations

Having training data that matches the diversity of your task is paramount to the success of your models. At Roboflow, we’re committed to providing you with state-of-the-art techniques that can improve your deep learning model’s performance -- without needing to collect any more data or even re-label images.

LabelImg for Labeling Object Detection Data

16 Mar 2020 • 3 min read

LabelImg for Labeling Object Detection Data

Accurately labeled data is essential to successful machine learning, and computer vision is no exception. In this walkthrough, we’ll demonstrate how you can use LabelImg to get started with labeling your own data for object detection models. Label and Annotate Data with Roboflow for free Use Roboflow to manage

The Importance of Blur as an Image Augmentation Technique

13 Mar 2020 • 3 min read

The Importance of Blur as an Image Augmentation Technique

Learn about the efficacy of blur as an image augmentation step in computer vision model training.

Training a TensorFlow Faster R-CNN Object Detection Model on a Custom Dataset

11 Mar 2020 • 9 min read

Training a TensorFlow Faster R-CNN Object Detection Model on a Custom Dataset

Following this tutorial, you only need to change a couple lines of code to train an object detection model to your own dataset. Computer vision is revolutionizing medical imaging. Algorithms are helping doctors identify 1 in ten cancer patients they may have missed. There are even early indications that radiological

Why to Add Noise to Images for Machine Learning

9 Mar 2020 • 3 min read

Why to Add Noise to Images for Machine Learning

Learn why adding noise can be effective as an image augmentation in computer vision modeling.

types

27 Feb 2020 • 4 min read

How to Select the Right Computer Vision Model Architecture

The success of your machine learning model starts well before you ever begin training. Ensuring you have representative images, high quality labels, appropriate preprocessing steps, and augmentations to guard against overfitting all affect deep learning model performance well before you begin training. And this is where Roboflow Organize comes in

Introducing an Improved PlantDoc Dataset for Plant Disease Object Detection

25 Feb 2020 • 3 min read

Introducing an Improved PlantDoc Dataset for Plant Disease Object Detection

The world population is expected to reach 9.7 billion by 2050. That’s a lot of mouths to feed. Technology is powering the next generation of yield increases. Computer vision is especially critical to greener, more efficient production. For example, Blue River’s (John Deere) “See & Spray [https:

Why and How to Implement Random Crop Data Augmentation

21 Feb 2020 • 4 min read

Why and How to Implement Random Crop Data Augmentation

Learn how to apply a random crop data augmentation to images for use in training computer vision models.

pioneer leaderboard

20 Feb 2020 • 2 min read

How to Win Pioneer

Pioneer.app is an online startup accelerator where companies are chosen based (partially) on weekly peer-review of progress updates. Roboflow has now been #1 on the global leaderboard for 18 consecutive weeks. In this post, I'm going to reveal our secrets and tell you how you can dethrone

Releasing an Improved Blood Count and Cell Detection (BCCD) Dataset

14 Feb 2020 • 1 min read

Releasing an Improved Blood Count and Cell Detection (BCCD) Dataset

Computer vision is revolutionizing medical diagnoses by assisting doctors with patterns they may not have seen or identifying an error they may have overlooked. Thus, it's unsurprising one of the more popular "hello world" datasets of object detection is the blood count and cell detection dataset

boilerplate

12 Feb 2020 • 4 min read

Eliminating Boilerplate Code with Roboflow to Monitor Security Camera Footage

By using Roboflow, data scientist Alaa Senjab reduced his time to train a custom object detection model detecting guns in security camera footage while increasing machine learning model accuracy. Highlights: * Validating image annotation quality, and automated correction of error-inducing improper labels * Preprocessing and augmentation techniques improving model generalizability * Automated generation

A popular self-driving car dataset is missing labels for hundreds of pedestrians

11 Feb 2020 • 2 min read

A popular self-driving car dataset is missing labels for hundreds of pedestrians

And that's a problem that is extremely dangerous. Machine learning, the process of teaching computer algorithms to perform new tasks by example, is poised to transform industries from agriculture [https://www.forbes.com/sites/bernardmarr/2019/03/15/the-amazing-ways-john-deere-uses-ai-and-machine-vision-to-help-feed-10-billion-people/] to insurance [https://news.microsoft.com/apac/features/ai-takes-the-pain-out-of-car-insurance-in-india/

Training a TensorFlow MobileNet Object Detection Model with a Custom Dataset

9 Feb 2020 • 7 min read

Training a TensorFlow MobileNet Object Detection Model with a Custom Dataset

Change two lines of code and have a custom trained object detection model leveraging the TensorFlow 1.5 API.

public

27 Jan 2020 • 2 min read

Introducing Public Datasets

One of the most painstaking components of getting started with computer vision is getting access to clean, labeled data. For example, when the Roboflow team built BoardBoss, we painstakingly collected hundreds of Boggle board images from various devices (iPhone 7, iPhone X, iPhone 11…) and then labeled each individual letter

Training a YOLOv3 Object Detection Model with a Custom Dataset

9 Jan 2020 • 11 min read

Training a YOLOv3 Object Detection Model with a Custom Dataset

A walkthrough of building chess piece object detection model, easily adapted to your own dataset.

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