This paper is published in Volume-7, Issue-4, 2021
Area
Convolutional Neural Network
Author
Nihal Kumar Singh, Aakash Singh, Ashish Prasad, S. Usha
Org/Univ
RajaRajeswari College of Engineering, Bengaluru, Karnataka, India
Pub. Date
09 August, 2021
Paper ID
V7I4-1511
Publisher
Keywords
Object Detection, Tensorflow, Opencv, Python, Tensorboard, R-CNN

Citationsacebook

IEEE
Nihal Kumar Singh, Aakash Singh, Ashish Prasad, S. Usha. Object segregation using R-CNN, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Nihal Kumar Singh, Aakash Singh, Ashish Prasad, S. Usha (2021). Object segregation using R-CNN. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Nihal Kumar Singh, Aakash Singh, Ashish Prasad, S. Usha. "Object segregation using R-CNN." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

Computer vision is the science of computers and pack-age systems that can also recognize how images and scenes are perceived. PC Vision consists of a variety of solutions that include image recognition, object recognition, image generation, super-resolution of images, and much more. widely used in facial recognition, vehicle recognition, pedestrian counting, network mapping, security systems, and autonomous cars, but here we have a tendency to specialize in completely different sensible objects, those with different kinds of fruits, buttons, coins, etc. In this project, we use extremely correct object recognition algorithms and methods like RCNN, FastRCNN, FasterRCNN, Mobilnet, and fast but extremely correct methods like SSD. If we understand frameworks by using dependencies like TensorFlow, OpenCV, etc., we can recognize every single object in the image through the realm object in a highlighted area and determine every single object and assign its label to the object. This also includes the precision of every technique used to distinguish between objects.