Publications
Here you can find a list of my peer-reviewed publications. For the most up-to-date list, please refer to my Google Scholar profile.
Journal Articles
- Machine learning for the estimation of cod from uv-vis spectrometer in leather industries wastewater. (2023)
Cardia, M., Chessa, S., Franceschi, M., Gambineri, F., & Micheli, A.
International Journal of Environmental Pollution and Remediation, 11, 10-19.
Conference Proceedings
Cardia, Marco, et al. “A Descriptive Review of Image Datasets for Accessible Alternative Descriptions in STEM Domains.” Proceedings of the 16th Biannual Conference of the Italian SIGCHI Chapter. 2025.
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A Descriptive Review of Image Datasets for Accessible Alternative Descriptions in STEM Domains. Cardia, M., Buzzi, M., Galesi, G., & Leporini, B. In Proceedings of the 16th Biannual Conference of the Italian SIGCHI Chapter (CHItaly 2025), ACM
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Water quality estimation through machine learning multivariate analysis. (2024)
Cardia, M., Chessa, S., Micheli, A., Luminare, A. G., & Gambineri, F.
In 34th Italian Workshop on Neural Nets (WIRN 2024), Springer. -
Hybrid cnn-mlp for wastewater quality estimation. (2024)
Cardia, M., Chessa, S., Micheli, A., Luminare, A. G., & Gambineri, F.
In International Conference on Artificial Neural Networks (pp. 198-212), Springer. -
Wastewater quality indicator estimation using machine learning and data augmentation techniques. (2024)
Cardia, M., Chessa, S., Micheli, A., Luminare, A. G., & Gambineri, F.
In International conference on soft computing models in industrial and environmental applications (pp. 47–57). -
Multitarget wastewater quality assessment in a smart industry context. (2024)
Cardia, M., Chessa, S., Micheli, A., Luminare, A. G., Franceschi, M., & Gambineri, F.
In 20th International Conference on Intelligent Environments (IE), IEEE. -
Estimation of cod from uv-vis spectrometer exploiting machine learning in leather industries wastewater. (2023)
Cardia, M., Chessa, S., Franceschi, M., Gambineri, F., & Micheli, A.
In Proceedings of the 8th world congress on civil, structural, and environmental engineering. -
Enhancing crowd flow prediction in various spatial and temporal granularities. (2022)
Cardia, M., Luca, M., & Pappalardo, L.
In Companion proceedings of the web conference 2022 (pp. 1251-1259).