Image Classification Versus Object Detection Versus Semantic Segmentation

The video tutorial covers three main types of computer vision solutions: image classification, object detection, and semantic segmentation. Image classification involves identifying the primary object in an image using a trained model. Object detection extends this by locating objects within an image and providing their coordinates. Semantic segmentation further advances object detection by associating each pixel with a tagged object. The tutorial also discusses practical applications and provides interactive scenarios to reinforce understanding.

How does the model identify the primary object in an image during classification?

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What role does Azure play in the context of image classification?

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In what ways can object detection enhance the capabilities of computer vision?

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What is the significance of bounding box coordinates in object detection?

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