Computer vision

Build computer vision AI faster with high-quality AI data

AI requires data

Computer Vision is the field of artificial intelligence that trains computers to interpret and understand the visual world. Visual information captured by cameras is converted into data using deep learning algorithms, which is then analyzed for patterns.

By using annotated or labeled images to train machine learning algorithms, machines can accurately identify and classify objects and then respond to what they "see". The massive amount of data that is generated today is helping drive the adoption of this technology. Computer vision applications can automate a wide range of manual tasks with a high degree of accuracy, freeing up time for work that is more suitable for humans.

Computer vision applications are currently being applied across a wide range of industries, including:

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Agriculture

Monitor crops and yields, detect insects and perform aerial surveys and imaging.
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Healthcare

Analyze CT scans, MRIs and X-rays, and detect cancer.
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Manufacturing

Inspect for defects, assemble products and ensure workplace safety.
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Retail

Use for self-checkout, inventory management and customer journey mapping.
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Transportation

Enable self-driving cars, analyze traffic flow and monitor road conditions.
Annotation & Enhancement - AI Data

Data to power your computer vision applications

LXT can help ensure that your computer vision applications get the high-quality data they need to deliver highly accurate predictions. Through our customized data collection and data annotation services we can help create the data pipeline you need to deliver best-in-class computer vision for your customers.

Learn more about our data services for computer vision

Data
collection

Get large volumes of data fast across multiple data types, including speech, text, image and video.
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Image
annotation

Image annotation is the process of creating metadata in the form of labels for image data.
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Video
annotation

Video annotation is the process of creating metadata in the form of labels for video clips.
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