Real-Time CCTV Based Garbage Detection for Modern Societies using Deep Convolutional Neural Network with Person-Identification-Reference-Cited by-同舟云学术

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Real-Time CCTV Based Garbage Detection for Modern Societies using Deep Convolutional Neural Network with Person-Identification

Published:2024-06-30 Issue:2 Volume:22 Page:109-120
ISSN:2234-8883
Container-title:Journal of information and communication convergence engineering
language:en
Short-container-title:JICCE

Author:

Raza Syed Muhammad¹^ORCID,Hassan Syed Ghazi²^ORCID,Hassan Syed Ali³^ORCID,Shin Soo Young¹^ORCID

Affiliation:

1. Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi-si 39177, Republic of Korea

2. Department of Computing and Information Sciences, Karachi Institute of Economics and Technology, Karachi 75190, Pakistan

3. Department of Bio Robotics, Scuola Superiore Sant'Anna, Pisa 56127, Italy

Funder

National Research Foundation of Korea

Ministry of Education, Science and Technology

Ministry of Science and ICT, South Korea

Iran Telecommunication Research Center

Publisher

Korea Institute of Information and Communication Engineering

Link

https://pdf.medrang.co.kr/JICCE/2024/022/JICCE022-02-109.pdf

Reference52 articles.

1. Air Index Quality Report for annual garbage collection, IQAir [Online], Available: https://www.iqair.com/pakistan. (Accessed 08 December 2021).

2. A Computer Vision Based Detection System for Trash Bins Identification during Trash Classification

3. Real-time UAV Detection based on Deep Learning Network

4. An Improved Deep Convolutional Neural Network-Based Autonomous Road Inspection Scheme Using Unmanned Aerial Vehicles

5. M. Yang and G. Thung, “Classification of trash for recyclability status,” CS229 project report, vol. 2016, no. 1, 2016.

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