VISUAL ANALYTICS AT SCALE TO MONITOR ENVIRONMENTS
Object Detection
Find multiple objects in a photo and learn more about them by identifying their locations.
Image Classification
Large data sets are used to power computer vision apps while labelling your photographs and taking control of your training data.
Object Segmentation
The process of splitting up an object into a collection of smaller fixed-size objects in order to optimize storage and resource usage for large objects.
Optical character recognition
OCR services convert data into automatically editable text by machines. OCR enables quick, precise, and effective data conversion of the highest calibre.
Object Tracking
The process of automatically locating objects in a video and accurately interpreting their collection of trajectories is known as object tracking.
Video Analytics
Using trained AI models, find and extract items from videos, then classify each object to enable intelligent video analysis.
Computer vision is a branch of artificial intelligence and deep learning where humans train computers to perceive and comprehend their surroundings. Helping robots comprehend and sense their surroundings through vision is still an issue that is mostly unsolved, despite the fact that people and animals naturally solve vision as a problem from a very young age.
Artificial intelligence (AI) is used in computer vision to teach computers how to decipher and comprehend the visual environment. Machines can properly recognise and classify items using digital images from cameras and videos, deep learning models, and then respond to what they “see”.
Our minimal knowledge of how the human brain and visual system function is one of the main obstacles in machine vision. We are unable to explain how we interpret what we see, despite having an increased and complicated sense of vision that we can grasp at a very young age.
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