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ENS6126 :proposal and risk assessment report

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ENS6126 Master of Engineering ...

Answer: Introduction Generally Transformers are considered as a most reliable unit, but there is a chance of failure because of internal fault, due to stresses from external sources. Fuse has been ...

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ENS6126 Master of Engineering ...

Task Guidelines on Progress Report   Last Revision: 03 Feb 2020 Purpose As you know, the Project is carried out across two units. You need to demonstrate that you have made adequate progress ...

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Implementing a sensor fusion a ...

Abyarjoo, F., Barreto, A., Cofino, J., & Ortega, F. R. (2015). Implementing a sensor fusion algorithm for 3D orientation detection with inertial/magnetic sensors. In Innovations and advances in compu ...

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Sensor fusion algorithm design ...

Kim, S., Kim, H., Yoo, W., & Huh, K. (2016). Sensor fusion algorithm design in detecting vehicles using laser scanner and stereo vision. IEEE Transactions on Intelligent Transportation Systems, 17(4 ...

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Sensor fusion methodology for ...

Garcia, F., Martin, D., De La Escalera, A., & Armingol, J. M. (2017). Sensor fusion methodology for vehicle detection. IEEE Intelligent Transportation Systems Magazine, 9(1), 123-133. ...

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Sensor fusion for semantic seg ...

Zhang, R., Candra, S. A., Vetter, K., & Zakhor, A. (2015, May). Sensor fusion for semantic segmentation of urban scenes. In 2015 IEEE International Conference on Robotics and Automation (ICRA) (pp. ...

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Multi-sensor fusion in body se ...

Gravina, R., Alinia, P., Ghasemzadeh, H., & Fortino, G. (2017). Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges. Information Fusion, 35, 68-80. ...

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Assessing the performance of s ...

Ligorio, G., Bergamini, E., Pasciuto, I., Vannozzi, G., Cappozzo, A., & Sabatini, A. (2016). Assessing the performance of sensor fusion methods: Application to magnetic-inertial-based human body track ...

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Heterogeneous data fusion algo ...

Fourati, H. (2015). Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter. IEEE Transactions on Instrumentation and Measure ...

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Smartphone GPS tracking—Inex ...

Korpilo, S., Virtanen, T., & Lehvävirta, S. (2017). Smartphone GPS tracking—Inexpensive and efficient data collection on recreational movement. Landscape and Urban Planning, 157, 608-617. ...

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Performance evaluation of cuba ...

Zhao, Y. (2016). Performance evaluation of cubature Kalman filter in a GPS/IMU tightly-coupled navigation system. Signal Processing, 119, 67-79. ...

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A cascaded Kalman filter-based ...

Zihajehzadeh, S., Loh, D., Lee, T. J., Hoskinson, R., & Park, E. J. (2015). A cascaded Kalman filter-based GPS/MEMS-IMU integration for sports applications. Measurement, 73, 200-210. ...

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Referencing Related to ENS6126 proposal and risk assessment report

KIM, S., KIM, H., YOO, W., & HUH, K. (2016)

Sensor Fusion Algorithm Design In Detecting Vehicles Using Laser Scanner And Stereo Vision. 

In-text: ((Huh,2016))

Your Bibliography: Kim, S., Kim, H., Yoo, W., & Huh, K. (2016). Sensor fusion algorithm design in detecting vehicles using laser scanner and stereo vision. IEEE Transactions on Intelligent Transportation Systems, 17(4), 1072-1084.

GARCIA, F., MARTIN, D., DE LA ESCALERA, A., & ARMINGOL, J. M. (2017).

Sensor Fusion Methodology For Vehicle Detection. 

In-text: ((Armingol,2017))

Your Bibliography: Garcia, F., Martin, D., De La Escalera, A., & Armingol, J. M. (2017). Sensor fusion methodology for vehicle detection. IEEE Intelligent Transportation Systems Magazine, 9(1), 123-133.

ZHANG, R., CANDRA, S. A., VETTER, K., & ZAKHOR, A. (2015)

Sensor Fusion For Semantic Segmentation Of Urban Scenes.

In-text: ((Zakhor,2015))

Your Bibliography: Zhang, R., Candra, S. A., Vetter, K., & Zakhor, A. (2015, May). Sensor fusion for semantic segmentation of urban scenes. In 2015 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1850-1857). IEEE.

GRAVINA, R., ALINIA, P., GHASEMZADEH, H., & FORTINO, G. (2017).

Multi-sensor Fusion In Body Sensor Networks: State-of-the-art And Research Challenges.

In-text: ((Alinia,2017))

Your Bibliography: Gravina, R., Alinia, P., Ghasemzadeh, H., & Fortino, G. (2017). Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges. Information Fusion, 35, 68-80.

LIGORIO, G., BERGAMINI, E., PASCIUTO, I., VANNOZZI, G., CAPPOZZO, A., & SABATINI, A. (2016).

Assessing The Performance Of Sensor Fusion Methods: Application To Magnetic-inertial-based Human Body Tracking. 

In-text: ((Cappozzo,2016))

Your Bibliography: Ligorio, G., Bergamini, E., Pasciuto, I., Vannozzi, G., Cappozzo, A., & Sabatini, A. (2016). Assessing the performance of sensor fusion methods: Application to magnetic-inertial-based human body tracking. Sensors, 16(2), 153.

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