Zobrazeno 1 - 10
of 767
pro vyhledávání: '"Waste classification"'
Publikováno v:
Management of Environmental Quality: An International Journal, 2024, Vol. 35, Issue 7, pp. 1545-1570.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/MEQ-09-2023-0319
Publikováno v:
Waste Management Bulletin, Vol 2, Iss 4, Pp 184-193 (2024)
The increasing volume of solid waste generated globally necessitates efficient classification systems to enhance recycling and waste management processes. Convolutional Neural Networks (CNNs) have emerged as a powerful tool for image classification t
Externí odkaz:
https://doaj.org/article/71be3b5435844f83ad3984771f3477b1
Autor:
Li, Huijie, Tan, Deqing
Publikováno v:
Kybernetes, 2023, Vol. 53, Issue 6, pp. 2069-2089.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/K-12-2022-1687
Publikováno v:
Frontiers in Environmental Science, Vol 12 (2024)
Introduction: The deviation between the stated intentions and actual actions of rural residents regarding waste classification constitutes a significant impediment to the effective implementation of environmental management strategies in rural areas.
Externí odkaz:
https://doaj.org/article/75f4bcca791d432184ebad61157d84de
Autor:
Ananya Ghosh, Parthiban Krishnamoorthy
Publikováno v:
IEEE Access, Vol 12, Pp 135040-135062 (2024)
Federated learning presents a potent avenue for addressing challenges in waste classification, where diverse datasets are distributed across sources. This paper introduces the Federated Average Knowledge Distilled Mutual Conditional Learning (FedADC)
Externí odkaz:
https://doaj.org/article/69cd5693c9854d97b3f2b57400377a9c
Autor:
Md. Mosarrof Hossen, Molla E. Majid, Saad Bin Abul Kashem, Amith Khandakar, Mohammad Nashbat, Azad Ashraf, Mazhar Hasan-Zia, Ali K. Ansaruddin Kunju, Saidul Kabir, Muhammad E. H. Chowdhury
Publikováno v:
IEEE Access, Vol 12, Pp 13809-13821 (2024)
In response to the growing waste problem caused by industrialization and modernization, the need for an automated waste sorting and recycling system for sustainable waste management has become ever more pressing. Deep learning has made significant ad
Externí odkaz:
https://doaj.org/article/586c1542cd294174856d8614c260d490
Autor:
Paola Vallejo, Daniel Correa, Juan Carlos Arbeláez, Marta S. Tabares, Santiago Ruiz-Arenas, Elizabeth Rendon-Velez, David Ríos-Zapata, Joan Alvarado
Publikováno v:
SoftwareX, Vol 26, Iss , Pp 101684- (2024)
One challenge in creating commercial solutions with supervised deep learning is acquiring large, customized labeled datasets. These datasets must often fit within commercial industries’ production times and budgets. There is still a need for target
Externí odkaz:
https://doaj.org/article/0ea8a56b0bb5464ab867706a21ecf7dd
Autor:
Wahidur Rahman, Mohona Akter, Nahida Sultana, Maisha Farjana, Arfan Uddin, Md. Bakhtiar Mazrur, Mohammad Motiur Rahman
Publikováno v:
Data in Brief, Vol 53, Iss , Pp 110153- (2024)
The “BDWaste” dataset contains two significant categories of waste, namely digestible and indigestible, in Bangladesh. Each category represents 10 distinct species of waste. The digestible categories are sugarcane husk, fish ash, potato peel, pap
Externí odkaz:
https://doaj.org/article/8ae63907e4c04c5b99945bd2d3a93082
Autor:
Justyna Rogowska, Agnieszka Zimmermann
Publikováno v:
Farmacja Polska, Vol 79, Iss 5, Pp 251-258 (2023)
The issue of waste is a topic widely discussed at both European and national levels. The insufficient share of separately collected waste in the stream and the too large amount of waste sent to landfills, combined with the need for Poland to implemen
Externí odkaz:
https://doaj.org/article/2d7fba3826154b8ba9c58a5a7695cfa1
Publikováno v:
Visual Computing for Industry, Biomedicine, and Art, Vol 6, Iss 1, Pp 1-9 (2023)
Abstract Waste pollution is a significant environmental problem worldwide. With the continuous improvement in the living standards of the population and increasing richness of the consumption structure, the amount of domestic waste generated has incr
Externí odkaz:
https://doaj.org/article/30b6521cab904ad19c4ef117ad0dd48a