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?

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

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

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