Mazhar Hussain
Universitetsadjunkt
- Tjänstetitel: Universitetsadjunkt
- Telefon arbete: +46 (0)10-1428748
- E-postadress: mazhar.hussain@miun.se
- Rumsnummer: S239d
- Ort: Sundsvall
- Sensible Things that Communicate, STC
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Forskningscentra:
Publikationer
Artiklar i tidskrifter
Konferensbidrag
Dataset
Artiklar i tidskrifter
Hussain, M. , O'Nils, M. , Lundgren, J. & Shallari, I. (2022). A Study on the Correlation between Change in the Geometrical Dimension of a Free-Falling Molten Glass Gob and Its Viscosity. Sensors, vol. 22: 2, ss. 661-661.
Hussain, M. , O'Nils, M. & Lundgren, J. (2021). Multi-Camera Based Setup for Geometrical Measurement of Free-Falling Molten Glass Gob. Sensors, vol. 21: 4
Konferensbidrag
Hussain, M. , O'Nils, M. , Lundgren, J. , Akbari-Saatlu, M. , Hamrin, R. & Mattsson, C. (2023). A Deep Learning Approach for Classification and Measurement of Hazardous Gases Using Multi-Sensor Data Fusion. I 2023 IEEE Sensors Applications Symposium (SAS).
Hussain, M. , Franked, L. & Björkqvist, O. (2023). Experiences of using LMS tools for implementing asynchronous interactive media to enhance student interaction in distance education. I Bidrag från den 9:e utvecklingskonferensen för Sveriges ingenjörsutbildningar. Västerås : . S. 287--295.
Shallari, I. , Gallo, V. , Carratu, M. , O'Nils, M. , Liguori, C. & Hussain, M. (2022). Image Scaling Effects on Deep Learning Based Applications. I 2022 IEEE International Symposium on Measurements & Networking (M&N).
Hussain, M. , O'Nils, M. , Lundgren, J. , Carratú, M. & Shallari, I. (2022). Selection of optimal parameters to predict fuel consumption of city buses using data fusion. I 2022 IEEE Sensors Applications Symposium (SAS).
Dataset
Hussain, M. (2023). Multi-sensor dataset for normal air, Methyl Mercaptan and Hydrogen Sulfide gas classification.