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Computer Vision is the technology which enables a computer to understand and analyze the visual things such as images, videos, etc.
There are many Computer Vision technologies as shown below:
(1) Classification(Recognition):
- can classify an entire image, video, etc into one or more classes(labels) from one or more classes(labels).
- can be more specifically called Image Classification(Recognition), Video Classification(Recognition), Object Classification(Recognition), etc.
- has the method Single-Label Classification which has two methods Binary Classification and Multi-Class Classification.
- has the method Multi-Label Classification.
*Memos:
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Binary Classification can classify an entire image, video, etc into a single class(label) from two classes(labels).
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Multi-Class Classification can classify an entire image, video, etc into a single class(label) from more than two classes(labels).
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Multi-Label Classification can classify an entire image, video, etc into multiple classes(labels) from more than two classes(labels).
(2) Localization:
- can localize the multiple objects and interesting regions in an image, video, etc with bounding boxes.
- can be more specifically called Image Localization and Video Localization, Object Localization, etc.
(3) Detection:
- can localize and classify the objects and interesting regions in an image, video, etc with classes(labels) and bounding boxes.
- is the combination of Object Localization and Classification(Recognition).
- can be more specifically called Image Detection, Video Detection, Object Detection, etc.
(4) Segmentation:
- can do Object Detection more precisely, differentiating stuff and things with colors:
*Memos:
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Stuff is uncountable things(classes) such as sky, sea, forrest, road, grass, landscape, etc.
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Things are countable things(classes) such as car, tree, person, animal, flower, etc.
- can be more specifically called Image Segmentation and Video Segmentation, Object Segmentation, etc.
- has the popular methods Semantic Segmentation, Instance Segmentation and Panoptic segmentation:
*Memos:
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Semantic Segmentation is good at differentiating stuff but not good at differentiating things.
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Instance Segmentation is good at differentiating things but not good at differentiating stuff.
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Panoptic segmentation:
- is good at differentiating both stuff and things.
- is the combination of Semantic Segmentation and Instance Segmentation.
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