All Outputs (3)

Optimizing the Parameters of Relay Selection Model in D2D Network (2024)
Conference Proceeding
Bunu, S. M., Saraee, M., & Alani, O. (2024). Optimizing the Parameters of Relay Selection Model in D2D Network. . https://doi.org/10.1109/ISRITI60336.2023.10467664

The Fifth generation (5G) cellular network's traffic load is certain to expand significantly in the near future as a result of its flexibility, high speed, increased bandwidth, better connectivity and low latency. Consequently, it is necessary to inv... Read More about Optimizing the Parameters of Relay Selection Model in D2D Network.

Multiclass Classification and Defect Detection of Steel tube using modified YOLO (2023)
Conference Proceeding
Saraee, M., & khan, S. (2023). Multiclass Classification and Defect Detection of Steel tube using modified YOLO.

Steel tubes are widely used in hazardous high pressure environments such as petroleum, chemicals, natural gas and shale gas. Defects in steel tubes have serious negative consequences. Using deep learning object recognition to identify and detect defe... Read More about Multiclass Classification and Defect Detection of Steel tube using modified YOLO.

LIFT the AV: Location InFerence aTtack on Autonomous Vehicle Camera Data (2023)
Conference Proceeding
Adeboye, O., Abdullahi, A., Dargahi, T., Babaie, M., & Saraee, M. (2023). LIFT the AV: Location InFerence aTtack on Autonomous Vehicle Camera Data. . https://doi.org/10.1109/ccnc51644.2023.10060796

Connected and autonomous vehicles (CAVs) are one of the main representatives of cyber-physical systems (CPS), where the digital data generated in several forms, such as geolocation, distance, and camera data, are used for the physical functionality o... Read More about LIFT the AV: Location InFerence aTtack on Autonomous Vehicle Camera Data.