Summary
Computer vision (CV) has many real-world applications. In this video, we cover examples of image classification, object detection, semantic segmentation, and activity recognition. Here's a brief summary of what you learn about each topic in the video:
- Image classification is the most common application of computer vision in use today. Image classification can be used to answer questions like What's in this image? This type of task has applications in text detection or optical character recognition (OCR) and content moderation.
- Object detection is closely related to image classification, but it allows users to gather more granular detail about an image. For example, rather than just knowing whether an object is present in an image, a user might want to know if there are multiple instances of the same object present in an image, or if objects from different classes appear in the same image.
- Semantic segmentation is another common application of computer vision that takes a pixel-by-pixel approach. Instead of just identifying whether an object is present or not, it tries to identify down the pixel level which part of the image is part of the object.
- Activity recognition is an application of computer vision that is based around videos rather than just images. Video has the added dimension of time and, therefore, models are able to detect changes that occur over time.
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