An Approach for Smart and cost-Efficient Automated E-Waste Recycling for Small to medium-Sized Devices Using multi-Sensors
Author:
Affiliation:
1. Ruhr West university of applied sciences,Computer science department,Bottrop,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9966996/9966997/09967195.pdf?arnumber=9967195
Reference19 articles.
1. Status quo of e-waste management in mainland China
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4. A Transfer Learning Evaluation of Deep Neural Networks for Image Classification
5. Techno-economic potential of recycling Tantalum containing capacitors by automated selective dismantling
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1. Towards a circular economy for electrical products: A systematic literature review and research agenda for automated recycling;Robotics and Computer-Integrated Manufacturing;2024-06
2. Transfer Learning Application for an Electronic Waste Image Classification System;The Palgrave Handbook of Sustainable Digitalization for Business, Industry, and Society;2024
3. KI-basierte Unterstützung beim automatisierten Elektroschrott-Recycling;Sustainable Development Goals (SDG) – Umsetzung in Praxis, Lehre und Entscheidungsprozessen;2024
4. E-Waste Recycling Gets Smarter with Digitalization;2023 IEEE Conference on Technologies for Sustainability (SusTech);2023-04-19
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