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Computer Vision

There are 5 posts filed in Computer Vision (this is page 1 of 1).

Loss Functions for Computer Vision Models

Choosing an appropriate loss function is important as it affects the ability of the algorithm to produce optimum results as fast as possible.

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Prerak Mody in Computer Vision, Machine Learning | Comment

Comparing Image Annotation Types by Computer Vision Use Cases

Pixel Perfect Annotation for Computer Vision

The most important thing that the computer vision expert does is to decide which annotation type is needed to build the most accurate model(s).

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Mothi Venkatesh in Computer Vision | Comment

What is Training Data, Really?

This is a simple definition of Training Data.

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Mothi Venkatesh in Computer Vision | Comment

A Definitive Guide To Build Training Data for Computer Vision

Training Data Meme from SiliconValley

I have briefly written about the ways you can start gathering training data. This depends majorly on the use case you plan to work on.

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Ajinkya in Computer Vision | Comment

Comparing the Top Computer Vision APIs for OCR

Top Computer Vision APIs for better OCR

Sunday Afternoon. You come across a magazine ad for solitaires, but it is the model wearing a perfect white sundress that catches your attention. What if you could take a picture of the dress and upload it, so an app could help you find a dress just like that one?

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Harish Choudhary in Computer Vision | 5 Comments
Training Data for AI - Playment
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