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At Over lab we specialize in the branch of artificial intelligence known as computer vision.Our goal is to help interpret AI algorithms to acquire, process, and understand visual data.In reality, that visual data comes in all forms from people to machinery to motor vehicles. But for us it comes as images, videos, or even 3D representations of data.
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Defining Computer Vision

Drone Autonomy

Drones are a useful tool that businesses can use in a variety of ways. Companies can use drones to inspect hard-to-reach places, monitor crops, locate inventory and much more.

The future of drones and artificial intelligence is bright, especially when you combine the two technologies together. Through Computer Vision, AI makes drones smarter and more useful than ever before.


AI can help drones predict and avoid upcoming problems. At The Over Lab we use CV to help drones learn new skills by gathering data and analyzing it.

This data can help create a machine learning model that enables a drone to learn and improve over time.

For example, you could use AI to train a drone to recognize the difference between a healthy and unhealthy crop. You could then have the drone use this data to monitor nearby crops and identify potential issues. 

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Image Captioning

The primary goal of image captioning is to describe an image with a text.

Our CV image captioning model understands the image content and generates relevant captions. Our model primarily consists of two parts:

  1. Content Extraction: Here we identify key aspects relevant to the content of the image. The extracted aspects are usually relevant to the content of the image. These key aspects can be a person, place, object, event, etc.

  2. Semantic Understanding: This is where our algorithms begin to understand the context of the image. Identifying the relationship between the different aspects of the image.

60% reduction in harmful emissions is said to be reported due to self-driving vehicles
(Ohio University)

Additional Applications

CV & Motor vehicles

Computer vision is already changing many aspects of our lives.

While computer vision is a crucial part of autonomous driving, it can also be used with regular driving.

For example, lane departure warning systems use computer vision to detect lane markings on the road. If the car begins to drift out of its lane, the system alerts the driver and makes the steering wheel vibrate.

Similarly, computer vision can be used for automatic emergency braking systems. If a car detects that it will collide with another vehicle, the computer vision system can automatically apply the brakes, which could prevent or mitigate the severity of a crash.

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