This article is part of a series on object recognition. The previous installment covered region-based object detection algorithms that are accurate but slow. This part focuses on fast object detection models, including SSD, RetinaNet, and those in the YOLO family. These models aim to balance speed and accuracy for applications like autonomous driving. --- Why it matters: Engineers working on autonomous vehicles need to know about these fast object detection models because they can be used to improve processing time without sacrificing too much accuracy. Source: https://lilianweng.github.io/posts/2018-12-27-object-recognition-part-4/