Region based CNN's - rugbyprof/5443-Data-Mining GitHub Wiki

Region of Interest

A region of interest (ROI) is a portion of an image that you want to filter or perform some other operation on.

Region proposal Algorithm

Region proposal algorithms identify prospective objects in an image using segmentation. In segmentation, we group adjacent regions which are similar to each other based on some criteria such as color, texture etc

Sliding Window

In the context of computer vision , a sliding window is rectangular region of fixed width and height that “slides” across an image.For each of these windows, we would normally take the window region and apply an image classifier to determine if the window has an object that interests us.

Selective search

Selective Search is a region proposal algorithm used in object detection. It is designed to be fast with a very high recall. It is based on computing hierarchical grouping of similar regions based on color, texture, size and shape compatibility.

Support Vector Machines(SVM)

In machine learning, support vector machines(SVM's) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.

PASCAL VOC Challenge

The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures.

Caffe (software)

Caffe is a deep learning framework, originally developed at UC Berkeley.Caffe supports many different types of deep learning architectures geared towards image classification and image segmentation. It supports CNN, RCNN, LSTM and fully connected neural network designs.

Intersection over Union(IoU)

Intersection over Union is an evaluation metric used to measure the accuracy of an object detector on a particular dataset.

histogram of oriented gradients (HOG)

The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method is similar to that of edge orientation histograms, scale-invariant feature transform descriptors, and shape contexts, but differs in that it is computed on a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy.

scale-invariant feature transform (SIFT )

The scale-invariant feature transform (SIFT) is a thing in computer vision to detect and describe local features in images

Neocognitron

The neocognitron is a hierarchical, multilayered artificial neural network proposed by Kunihiko Fukushima in the 1980s. It has been used for handwritten character recognition and other pattern recognition tasks, and served as the inspiration for convolutional neural networks