Region Based CNN (R-CNN)

R-CNN architecture is used to detect the classes of objects in the images and the bounding boxes of these objects. RCNN architecture has been developed since classification cannot be made for more than one object with CNN in visuals containing more than one object.

The general working principle of R-CNN takes place in two steps. First, the features where the object can be found in the visual are determined with selective search, then after the regions are determined, each region is given as an input to a CNN model and the prediction process is performed for classes and bounding boxes.


Darknet is an open source neural network framework developed with C and Cuda. Supports CPU and GPU calculations. Compatible with MacOS, Windows, Linux operating systems. However, some files and settings may need to be reconfigured in order to use this framework.
This article will talk about how to install Darknet on Ubuntu 20.04. First of all, if you want to run the Darknet framework on the GPU, you must have an Nvidia driver. Then you have to install Cuda and cuDNN. I could not find a source on the internet that contains detailed information about darknet usage in Ubuntu 20.04, that’s…

Sema Zeynep Bulut

Computer engineering student at Turkish German University

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