# R-CNN

2019-07-07

Computer Vision

2687

Overview
Regions with CNN features:
Efficient Graph Based Image Segmentation
use disjoint set to speed up merge operation
Selective Search
HOG (Histogram of Oriented Gradient)
Multiple criterions (color, texture, size, shape) to merge regions
AlexNet/VGG16
R-CNN
Notice that many descriptions are replicated from the orignal sources directly.
Some Fundermental Conceptions
Batch Size
Stochastic Gradient Descent. Batch Size = 1
Batch Gradient Descent. Batch Size = Size of Training Set
Mini-Batch Gradient Descent. 1 < Batch Size < Size of Training Set
Regularization
A regression model that uses L1 Regularization technique is called Lasso Regression and model which uses L2 is called Ridge Regression.
Ridge Regularization
Ridge regression adds "squared magnitude" of coefficient as penalty term to the loss function.
The first sum is an example of loss function.
Lasso Regularization
Lasso Regression (Least Absolute Shrinkage and Selection Operator) adds "absolute value of magnitude" of coefficient as penalty term to the loss function.