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Vision based relative position estimation in surgical robotics. (2023)
Conference Proceeding
MUTHUKRISHNAN, R., KANNAN, S., PRABHU, R., ZHAO, Y., BHOWMICK, P. and HASAN, M.J. 2023. Vision based relative position estimation in surgical robotics. In Proceedings of the 2023 Network, multimedia and information technology international conference (NMITCON 2023), 1-2 September 2023, Bengaluru, India. Piscataway: IEEE [online], article number 10275973. Available from: https://doi.org/10.1109/NMITCON58196.2023.10275973

Teleoperation-based Robotic-Assisted Minimally In-vasive Surgery (RAMIS) has gained immense popularity in medical field. However, limited physical interaction between the surgeon and patient poses a significant challenge. In RAMIS, the surgeon operat... Read More about Vision based relative position estimation in surgical robotics..

Tracking and estimation of surgical instrument position and angle in surgical robot using vision system. (2023)
Conference Proceeding
MUTHUKRISHNAN, R., KANNAN, S., PRABHU, R., ZHAO, Y., BHOWMICK, P. and HASAN, M.J. 2023. Tracking and estimation of surgical instrument position and angle in surgical robot using vision system. In Proceedings of the 2023 Network, multimedia and information technology international conference (NMITCON 2023), 1-2 September 2023, Bengaluru, India. Piscataway: IEEE [online], article number 10275983. Available from: https://doi.org/10.1109/NMITCON58196.2023.10275983

A da Vinci robot endoscopic-camera gives surgeons a magnified 2D view of the operating area, but additional time is required to detect and estimate the location of the surgical-instrument during an operation. The main focus and novelty of this resear... Read More about Tracking and estimation of surgical instrument position and angle in surgical robot using vision system..

Transfer learning with 2D vibration images for fault diagnosis of bearings under variable speed. (2022)
Conference Proceeding
AHMAD, Z., HASAN, M.J. and KIM, J.-M. 2022. Transfer learning with 2D vibration images for fault diagnosis of bearings under variable speed. In Abraham, A., Gandhi, N., Hanne, T., Hong, T.-P., Rios, T.N. and Ding, W. (eds.) Intelligent systems design and applications: proceedings of 21st International conference on intelligent systems design and applications (ISDA 2021), 13-15 December 2021, [virtual event]. Lecture notes in networks and systems, 418. Cham: Springer [online], pages 154-164. Available from: https://doi.org/10.1007/978-3-030-96308-8_14

One of the most critical assignments in fault diagnosis is to decide the finest set of features by evaluating the statistical parameters of the time-domain signals. However, these parameters are vulnerable under variable speed conditions, i.e., diffe... Read More about Transfer learning with 2D vibration images for fault diagnosis of bearings under variable speed..

Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed. (2019)
Conference Proceeding
HASAN, M.J. and KIM, J. 2020. Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed. In Djeddi, C., Jamil, A. and Siddiqi, I. (eds.) Pattern recognition and artificial intelligence: proceedings of the 3rd Mediterranean conference on pattern recognition and artificial intelligence (MedPRAI 2019), 22-23 December 2019, Istanbul, Turkey. Communications in computer and information science (CCIS), 1144. Cham: Springer [online], pages 106-117. Available from: https://doi.org/10.1007/978-3-030-37548-5_9

For industrial safety, correct classification of gearbox fault conditions is necessary. One of the most crucial tasks in data-driven fault diagnosis is determining the best set of features by analyzing the statistical parameters of the signals. Howev... Read More about Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed..

A novel modified SFTA approach for feature extraction. (2016)
Conference Proceeding
HASAN, M.J., UDDIN, J. and PINKU, S.N. 2016. A novel modified SFIA approach for feature extraction. In Proceedings of 3rd International conference on electrical engineering and information and communication technology 2016 (iCEEiCT 2016), 22-24 September 2016, Dhaka, Bangladesh. Piscataway: IEEE [online], article 7873115. Available from: https://doi.org/10.1109/CEEICT.2016.7873115

To increase the efficiency of conventional Segmentation Based Fractal Texture Analysis (SFTA), we propose a new approach on SFTA algorithm. We use an optimum multilevel thresholding hybrid method of Genetic Algorithm (GA) and Particle Swarm Optimizat... Read More about A novel modified SFTA approach for feature extraction..