Chapter 7 - Basics of Object Detection

1. How does the region proposal technique generate proposals?
   It identifies regions that are similar in color, texture, size, and shape.
2. How is IoU calculated if there are multiple objects in an image?
   IoU is calculated for each object with the ground truth, using Intersection Over Union metric
3. Why does R-CNN take a long time to generate predictions?
   Because we create as many forward propagations as there are proposals
4. Why is Fast R-CNN faster when compared to R-CNN?
   For all proposals, extracting the feature map from the VGG backbone is common. This reduces almost 90% of the computations as compared to Fast RCNN

5. How does RoI Pooling work?
   All the selectivesearch crops are passed through adaptive pooling kernel so that the final output is of the same size
6. What is the impact of not having multiple layers, post obtaining feature map, when predicting the bounding box corrections?
   You might not notice that the model did not learn to predict the bounding...