Object Detection & Segmentation
In some cases, you don’t want to assign categories or labels to images only, but want to detect objects. The main difference is that through detection, you can get the position of the object (bounding box), and you can detect multiple objects of the same type on an image. Therefore, your training data requires bounding boxes to mark the objects to be detected, but our sophisticated GUI can make this task a breeze. Or our professional content curators can help you! From a machine learning perspective, object detection is much more difficult than classification/labeling, but it depends on us.
Automated Categorization & Tagging of Images
Categorize & tag images with your own labels or detect objects
Highly Probable
OUTDOOR - 96.35%
RIVER - 91.50 %
BRIDGE - 87.55%
HOUSE - 81.20%
TREE - 75.66%
CLOUDS - 50.60%
Instant Launch
The key benefit of regular tagging is that you do not need to train your own model or upload any data. Just register and use our API to get predictions immediately. If you don't want the data to leave your computer, we can run it on the cloud and your own server.
Expanding the Tags
The tag set is the basis of any fast and simple AI system. However, if specific models require special labels for your own use cases, please feel free to contact us, we can extend them and adjust them to your actual needs. We can use new knowledge to expand your stock photo database and create a better search experience.
We are Experts Ready to Help You Out
Machine learning is our passion. We know the ins and outs of various technologies that can use all or part of automation to help you improve your business. Please feel free to contact us and tell us what we can do for you.
Technology Stack
We use the most advanced neural network models and machine learning techniques. Continuously try to improve the technology in order to always have the best quality. Each model has millions of parameters that can be processed by the CPU or GPU. Our intelligent algorithm selects and uses the best performing algorithm from multiple models.
1 - Define
Define your category and upload a sample image.
2 - Train
Define your category and upload a sample image.
3 - Recognize
Define your category and upload a sample image.
Typical Use Cases for Detection
Human & Face Detection
Detect people or faces and predict age, gender or more specific features in security camera lenses.
Satellite Imagery Analysis
Detect vehicles or other identifiable objects and calculate free parking spaces or predict fires.
Consumer Item Matching
Automatically detect consumer products in photos and find them in your e-commerce store.
Production Quality Control
Detect abnormalities and defects in the production line, and calculate the quality of the finished product.
Brand Tracking
Logo detection and brand visibility tracking in still photo camera photos or security lense s.
Explore similar AI-powered solutions that complement Image Recognition
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AI-powered deep learning for logistics automation.
We are Experts Ready to Help You Out
Machine learning is our passion. We know the ins and outs of various technologies that can use all or part of automation to help you improve your business. Please feel free to contact us and tell us what we can do for you.
Technology Stack
We use the most advanced neural network models and machine learning techniques. Continuously try to improve the technology in order to always have the best quality. Each model has millions of parameters that can be processed by the CPU or GPU. Our intelligent algorithm selects and uses the best performing algorithm from multiple models.
Talk to us about AI Image Recognition
[email protected] · +1 (442) 264-1012