Smart City Gnosys

Smart city article details

Title	A Deep Convolutional Neural Network For Classifying Waste Containers As Full Or Not Full
ID_Doc	1316
Authors	Fonseca B.J.; Felermino D.M.A.; Saide S.M.
Year	2019
Published	5th IEEE International Smart Cities Conference, ISC2 2019
DOI	http://dx.doi.org/10.1109/ISC246665.2019.9071746
Abstract	There is a common understanding that cleanliness is somehow proportional to the economic development of a country. Thus, in order to become clean, a country needs to have an efficient garbage monitoring system. One important component of such a system is garbage collection time because if we delay emptying the bins, the trash ends up to putting public health at risk. This paper is about creating a Deep Convolutional Neural Networks (DCNNs) based model for classifying a waste container as full or not, so that can be later on used by real-time garbage monitoring systems to process images acquired by cameras installed nearby the trash bins or smartphones. To achieve this, we trained and tested different well-known DCNNs architectures, namely, ResNet34, ResNet50, Inception-v4 and DarkNet53. The models were trained and tested using Repeated K-Fold Cross-Validation, running 5-Fold Cross-Validation 6 times. The results have showed that Inception-v4 outperformed the other models, with near-perfect results: PR-AUC =0.994, F1=0.988, Precision =0.989, Recall =0.987 and ACC =0.987. With these results can be said: a high Precision DCNNs based model was built. © 2019 IEEE.
Author Keywords	Artificial Neural Networks; Deep Learning; Image Classification; Pattern Recognition

Similar Articles

Id	Similarity	Authors	Title	Published
19352	0.938	Oğuz A.; Ertuğrul Ö.F.	Determining The Fullness Of Garbage Containers By Deep Learning	Expert Systems with Applications, 217 (2023)
22313	0.934	Chauhan R.; Shighra S.; Madkhali H.; Nguyen L.; Prasad M.	Efficient Future Waste Management: A Learning-Based Approach With Deep Neural Networks For Smart System (Lads)	Applied Sciences (Switzerland), 13, 7 (2023)
58934	0.92	Sultana R.; Adams R.D.; Yan Y.; Yanik P.M.; Tanaka M.L.	Trash And Recycled Material Identification Using Convolutional Neural Networks (Cnn)	Conference Proceedings - IEEE SOUTHEASTCON, 2020-March (2020)
1122	0.919	Saranya A.; Bhambri M.; Ganesan V.	A Cost-Effective Smart E-Bin System For Garbage Management Using Convolutional Neural Network	2021 International Conference on System, Computation, Automation and Networking, ICSCAN 2021 (2021)
11208	0.912	Kavitha R.; Yazhini S.	Automated Garbage Waste Management Using Deep Learning For Sustainability	2025 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2025 (2025)
58937	0.912	Jadhav R.; Mhaske A.; Nawale A.; Oswal M.; Mulhar S.	Trashintelai- Garbage Collection Automation Using Deep Learning And Image Processing	2023 Global Conference on Information Technologies and Communications, GCITC 2023 (2023)
27708	0.909	Suman S.; Kurmi S.K.; Diwakar M.; Pandey N.K.; Singh P.; Madaan P.	Garbage Classification And Analysis Using Deep Learning	2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025 (2025)
24046	0.909	Ahmed Khan H.; Naqvi S.S.; Alharbi A.A.K.; Alotaibi S.; Alkhathami M.	Enhancing Trash Classification In Smart Cities Using Federated Deep Learning	Scientific Reports, 14, 1 (2024)
58394	0.909	Islam M.; Hasan S.M.M.; Rakib H.; Uddin P.; Mamun A.	Towards Sustainable Solutions: Effective Waste Classification Framework Via Enhanced Deep Convolutional Neural Networks	PLOS ONE, 20, 6 June (2025)
7826	0.908	Saghana K.; Saranya P.; Mahesh Reddy A.; Keerthy Rai V.; Ramasubramanian B.; Sudhakaran P.	An Efficient Deep Learning Based Waste Management System For Sustainable Environment	3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025 (2025)