TY - JOUR
AU - 
AB - 8 VII July 2020 https://doi.org/10.22214/ijraset.2020.30585 International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429 Volume 8 Issue VII July 2020- Available at www.ijraset.com 1 2 3 4 5 Mekhla Tiwary , Ashish Kumar , Kaushal Kumar , Kavyashree Nayak K , Rajeshwari J 1, 2, 3, 4, 5 Information Science and Engineering Dayananda Sagar College of Engineering, Bangalore, India Abstract: The purpose of this paper is to develop a computer vision model using deep learning technique that can detect the different kind of waste. Waste disposal and its management are considered as an essential part in maintaining cleanliness in the cities. Waste management becomes easy if segregation of different kind of waste happens at initial level. The paper begins with analyzing advantages and disadvantages of existing smart bins that mainly focus on weight of the waste inside them. There are few proposed framework for waste segregation but a better and a strong model can be developed using deep learning. The goal is to come up with an optimized object detection architecture may be used for segregating three different kinds of waste that are normally generated, that is plastic, 
TI - Smart Bin using Machine Learning
JF - International Journal for Research in Applied Science and Engineering Technology
DO - 10.22214/ijraset.2020.30585
DA - 2020-07-31
UR - https://www.deepdyve.com/lp/unpaywall/smart-bin-using-machine-learning-IFKm10Daha
DP - DeepDyve
ER -