Jethro Odeyemi

Jethro Odeyemi

Lead Software Engineer at Roamlii and independent research scientist with interest machine learning, medical robotics, and human-computer interaction.

Publications

You can also find my articles on my Google Scholar profile.

A Novel Embryo Morphology Evaluation Based on Improved YOLOv8 Object Detection Model

Published in International Conference on Life System Modeling and Simulation, LSMS 2024 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024, Suzhou, China, 2025

This study presents a novel approach for embryo morphology evaluation using an improved YOLOv8 object detection model, offering significant advancements in the field of reproductive medicine. Read more

Recommended citation: Talha, O., Zhou, W., Xu, Y., Liu, Q., Odeyemi, J. (2024). A Novel Embryo Morphology Evaluation Based on Improved YOLOv8 Object Detection Model. In: Gu, J., Hu, F., Zhou, H., Fei, Z., Yang, E. (eds) Robotics and Autonomous Systems and Engineering Applications of Computational Intelligence. LSMS ICSEE 2024 2024. Communications in Computer and Information Science, vol 2220. Springer, Singapore. https://doi.org/10.1007/978-981-96-0313-8_15
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On Automated Object Grasping for Intelligent Prosthetic Hands Using Machine Learning

Published in Bioengineering, 2024

Prosthetic technology has witnessed remarkable advancements, yet challenges persist in achieving autonomous grasping control while ensuring the user’s experience is not compromised. Read more

Recommended citation: Odeyemi, J.; Ogbeyemi, A.; Wong, K.; Zhang, W. On Automated Object Grasping for Intelligent Prosthetic Hands Using Machine Learning. Bioengineering 2024, 11, 108. https://doi.org/10.3390/bioengineering11020108.
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Exploring the potential of computer vision and machine learning in enhancing the functionality of an EMG-controlled prosthetic hand

Published in Harvest, University of Saskatchewan, 2023

The potential of using machine learning techniques to develop prosthetic arms that can automatically perform hand gestures and grasp objects is very important in healthcare systems. Hands are an important part of the body for all vertebras, animals use theirs for locomotion, however, because of our bipedal nature as humans, we use our hands majorly for gripping and general manipulation. Read more

Recommended citation: Odeyemi, J. (2023). Exploring the potential of computer vision and machine learning in enhancing the functionality of an EMG-controlled prosthetic hand. Masters thesis, University of Saskatchewan.
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A human factor approach to distribution network design for e-commerce in supply chain system: a case study

Published in Enterprise Information Systems, 2023

Distribution network for e-commerce is an important supply chain (SC) networks required for effective management of warehousing. Due to the recent disruption in the SC, minimal lead times for product delivery days can no longer be guaranteed, thereby causing an increase in distribution and delivery of goods. Read more

Recommended citation: Ogbeyemi, A., Odeyemi, J., Igenewari, O., & Ogbeyemi, A. (2023). A human factor approach to distribution network design for e-commerce in supply chain system: a case study. Enterprise Information Systems, 17(12). https://doi.org/10.1080/17517575.2023.2200767.
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Deep machine learning for Sensing, Analysis, and Interpretation in IoT Healthcare

Published in Reinvention of Health Applications with IoT, 2022

The introduction of the Internet of Things (IoT) has brought about a much-needed upgrade in healthcare industry worldwide. As the world population continues to increase, data generated in these industries are now collected and transmitted seamlessly over the internet, leading to a more efficient system while reducing healthcare costs. Read more

Recommended citation: O.J. Odeyemi, S.O. Owoeye, K.I. Adenuga and C.B. Emele. (2022). Deep machine learning for Sensing, Analysis, and Interpretation in IoT Healthcare. Reinvention of health applications with IoT: 1-16.
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Deep data analysis for COVID-19 outbreak

Published in Reinvention of health applications with IoT, 2022

The rampaging effects of the coronavirus disease in 2019 (COVID-19), which was pronounced a pandemic on 11 March 2020 by the World Health Organization (WHO), have become one of the biggest challenges of the twenty-first century in terms of general wellbeing and safety. Read more

Recommended citation: O.J. Odeyemi, S.O. Owoeye, K.I. Adenuga and C.B. Emele. (2022). Deep machine learning for Sensing, Analysis, and Interpretation in IoT Healthcare. Reinvention of health applications with IoT: 1-16.
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