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Top 20 Image Datasets for Machine Learning and Computer Vision
This story was originally published on HackerNoon at: https://hackernoon.com/top-20-image-datasets-for-machine-learning-and-computer-vision-rq3w3zxo.
Computer vision enables computers to understand the content of images and videos. The goal in computer vision is to automate tasks that the human visual system can do.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #artificial-intelligence, #ai, #ml, #machine-learning, #data-science, #datasets, #dataset, #computer-vision, and more.
This story was written by: @limarc. Learn more about this writer by checking @limarc's about page,
and for more stories, please visit hackernoon.com.
Computer vision enables computers to understand the content of images and videos. The goal in computer vision is to automate tasks that the human visual system can do. The image data can come in different forms, such as video sequences, view from multiple cameras at different angles, or multi-dimensional data from a medical scanner. MIT has created a large dataset of 187,240 images, 62,197 annotated images, and 658,992 labeled objects. Google’s Open Images is a collection of 9 million URLs to images that have been annotated with labels spanning over 6,000 categories.
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This story was originally published on HackerNoon at: https://hackernoon.com/top-20-image-datasets-for-machine-learning-and-computer-vision-rq3w3zxo.
Computer vision enables computers to understand the content of images and videos. The goal in computer vision is to automate tasks that the human visual system can do.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #artificial-intelligence, #ai, #ml, #machine-learning, #data-science, #datasets, #dataset, #computer-vision, and more.
This story was written by: @limarc. Learn more about this writer by checking @limarc's about page,
and for more stories, please visit hackernoon.com.
Computer vision enables computers to understand the content of images and videos. The goal in computer vision is to automate tasks that the human visual system can do. The image data can come in different forms, such as video sequences, view from multiple cameras at different angles, or multi-dimensional data from a medical scanner. MIT has created a large dataset of 187,240 images, 62,197 annotated images, and 658,992 labeled objects. Google’s Open Images is a collection of 9 million URLs to images that have been annotated with labels spanning over 6,000 categories.