Training Data for Computer Vision & AI
The biggest difference between WebPurify and other computer vision training services is that we do not use crowdsourced employees to produce training datasets for AI. We have an in-house staff of trained professionals who work on everything from bounding boxes and keywording to visual search comparisons and content and media classification. Why? Because your AI system is only as smart as the information its given.
We don’t believe in crowdsourcing because it brings in an element of the unknown—who really knows who’s training your AI? An ill-trained employee can result in ill-functioning AI. (That’s obviously not what you want.) WebPurify’s quality service creates consistent data to train your computer vision algorithms, and we can scale our team and customize our service to meet your individual system’s image and video needs.
Artificial Intelligence Trained by Intelligent Humans
Algorithms require hundreds of thousands of human-guided examples to learn how best to function. WebPurify helps you generate these datasets to make your programs perfect:
Annotating images and video through bounding boxes can be a painstaking, time-consuming undertaking. The good news is: you don’t have to tag your own data! WebPurify takes the chore of drawing boxes around every part of an image or video and labeling them with what those items are off your shoulders.
Keywording images and videos is similar to bounding boxes, except it involves word “tagging” only, without the boxes. This is often a major undertaking for technology companies to do in-house. Let our experts handle training your AI to automatically detect each piece of images and videos.
Visual Search Comparisons
Visual search comparisons involve training a system to find similar images. For example, a retail brand might want its website to pull up related items alongside those which the user searches for. This also applies to faces in images, and instructing the AI “brain” to recognize people.
Content and Media Classification
Content and media classification trains your system to detect photos of a certain subject or category. For instance, if your app features photos of homes, it might need to discern between the rooms within the home so that when people search for a particular room, only those room categories are pulled up.
Sentiment analysis is where we train computers to detect the emotions—happy, sad, angry and more—of people in images and videos. We’ll categorize thousands of visuals and use them to instruct your AI to identify sentiments.
Armed with all of these avenues of training data for computer vision and a well-versed, professional team, your AI will be on point.
Ready to solve your computer vision training data problems?