From Image Classification to Object Detection
Explore the key differences between image classification and object detection. Learn how object detection combines locating objects with bounding boxes and classifying them. Understand the roles of classification and regression, and how techniques like linear, logistic, and softmax regression apply in detection tasks.
Image classification vs. object detection
While the image classification problem focuses on classifying the images, in object detection, there might be more than one object we’re searching for. Our task is to find all of them placed in the most appropriate boxes with their belonging classes. Therefore, our goal is relatively more complex than image classification. We have to first detect the objects by locating them with bounding boxes, then classify them to decide which class this box (thing) belongs to.
To sum up:
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Image classification: It predicts the class of an image.
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Object localization: It locates the presence of objects in an image and indicates their location with a bounding box.
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Object detection: It locates the presence of objects with a bounding box and detects the classes of the located objects in these ...