This paper is published in Volume-8, Issue-3, 2022
Area
Deep Learning
Author
Hanumanth K., S. Vidhayini, Pawan Sahu
Org/Univ
Jain University School of Engineering and Technology, Bangalore, Karnataka, India
Pub. Date
26 May, 2022
Paper ID
V8I3-1341
Publisher
Keywords
MobileNet Architecture, VGG16 model, Accuracy, Data collection, Convolutional Neural Network

Citationsacebook

IEEE
Hanumanth K., S. Vidhayini, Pawan Sahu. Waste Stratification using Deep Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Hanumanth K., S. Vidhayini, Pawan Sahu (2022). Waste Stratification using Deep Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 8(3) www.IJARIIT.com.

MLA
Hanumanth K., S. Vidhayini, Pawan Sahu. "Waste Stratification using Deep Learning." International Journal of Advance Research, Ideas and Innovations in Technology 8.3 (2022). www.IJARIIT.com.

Abstract

Waste management is one of the most serious problems that practically every country faces. Its goal is to offer sanitary, efficient, and costeffective solid waste storage, collection, transportation, treatment, and disposal without harming the environment, land, or water system. Waste sorting errors can result in incorrect disposal and the loss of opportunity to recycle or reuse items. Monitoring by hand is inefficient and costly. As a result, deep learning and machine learning play a critical role in categorizing and sorting garbage and rubbish, effectively distinguishing between different types of waste. Many tasks, such as garbage collection and waste classification/ segregation, are part of waste management. One of the most important operations is garbage classification, which is carried out in a variety of ways based on the nature of the material.