Transfer Learning Application for an Electronic Waste Image Classification System

Author:

Öztürk-Birim ŞuleORCID,Gündüz-Cüre MerveORCID

Publisher

Springer International Publishing

Reference55 articles.

1. Albawi, S., Mohammed, T. A., & Al-Zawi, S. (2017). Understanding of a convolutional neural network. In 2017 International conference on engineering and technology (pp. 1–6). https://doi.org/10.1109/ICEngTechnol.2017.8308186

2. Amin, Z. M. A., Sami, K. N., & Hassan, R. (2021). An approach of classifying waste using transfer learning method. International Journal on Perceptive and Cognitive Computing, 7(1), 41–52.

3. Baker, N. A., & Handmann, U. (2022). An approach for smart and cost-efficient automated e-waste recycling for small to medium-sized devices using multi-sensors. In 2022 IEEE sensors (pp. 1–4). https://doi.org/10.1109/SENSORS52175.2022.9967195

4. Baldé, C. P., D’Angelo, E., Luda, V., Deubzer, O., & Kuehr, R. (2022). Global transboundary e-waste flows monitor 2022. United Nations Institute for Training and Research (UNITAR).

5. Basel Convention. (2022). E-waste.

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