Deep Learning for Computer Vision

Summary

In this chapter, we have learned the difference between object localization and detection tasks. Several datasets and evaluation criteria were discussed. Various approaches to localization problems and algorithms, such as variants of R-CNN and SSD models for detection, were discussed. The implementation of detection in open-source repositories was covered.  We trained a model for pedestrian detection using the techniques. We also learned about various trade-offs in training such models.

In the next chapter, we will learn about semantic segmentation algorithms. We will use the knowledge to implement the segmentation algorithms for medical imaging and satellite imagery problems.