Research Article
A Deep Learning-Based Substructure for Trash Detection and Face Recognition
@INPROCEEDINGS{10.4108/eai.7-12-2021.2314723, author={AbigaSansuri M and Anusuya K.V and Nivethitha M}, title={A Deep Learning-Based Substructure for Trash Detection and Face Recognition}, proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India}, publisher={EAI}, proceedings_a={ICCAP}, year={2021}, month={12}, keywords={cleanliness face recognition litter detection mask - rcnn neural networks}, doi={10.4108/eai.7-12-2021.2314723} }- AbigaSansuri M
Anusuya K.V
Nivethitha M
Year: 2021
A Deep Learning-Based Substructure for Trash Detection and Face Recognition
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314723
Abstract
Traditional Street cleaning procedures demand larger manpower. It necessitates the identification of people who litter on the roadside using scientific approaches. In the proposed system, a deep neural network algorithm named Convolutional Neural Network (CNN), precisely Mask Region Convolutional Neural Network (MRCNN) is used a l o n g with t h e c a m e r as fixed a t t h e crowded areas such as bus stops and markets. This deep learning method is used in the suggested schema to evaluate the photos of streets and detect litter (if any) in them. The detection of litter further progresses with the identification of the person who has thrown it. This technique uses the built-in library files of Python, to generate and compare face encodings. Moreover, it is involved in assisting with better monitoring and reducing operational costs.