Papers by Usman Ibrahim Musa
Marine Robotics: An Improved Algorithm for Object Detection Underwater
Indian Journal of Computer Graphics and Multimedia
The visibility of items in water is lower than that of those on land. Light waves from a source d... more The visibility of items in water is lower than that of those on land. Light waves from a source don't have enough time to reach an item before it vanishes beneath the surface because light waves in water travel more quickly than they do in air. As a result, it can be challenging for people to deal with water properly due to certain of its physical characteristics. In light of this, object detection underwater has a wide range of uses, including environmental monitoring, surveillance, search and rescue, and navigation. This might enhance the precision, efficiency, and safety of undersea activities. In light of the aforementioned, this paper presents an algorithm for detecting objects underwater using YOLOv5. The algorithm has been improved by changing the way YOLOv5 works, which makes it better at detecting small objects. We tested our algorithm and found that it is more accurate than the original YOLOv5 algorithm.
International Research Journal of Engineering and Technology , 2023
This research paper explores the integration of AI algorithms to advance the technology of digita... more This research paper explores the integration of AI algorithms to advance the technology of digital twins. Digital twin is a virtual representation of a physical object, process, or system that enables real-time monitoring and analysis, which has the potential to transform various industries. However, despite its potential, the technology faces several challenges, such as data management, scalability, and accuracy. This paper proposes the use of AI algorithms to address these challenges and improve the performance of digital twin technology. The proposed AI algorithms can help overcome the challenges faced by digital twin technology, making it more scalable, accurate, and efficient. This paper provides a valuable contribution to the field of digital twin technology and offers insights into its potential applications and challenges.
Indian Journal of Computer Graphics and Multimedia , 2023
The visibility of items in water is lower than that of those on land. Light waves from a source d... more The visibility of items in water is lower than that of those on land. Light waves from a source don't have enough time to reach an item before it vanishes beneath the surface because light waves in water travel more quickly than they do in air. As a result, it can be challenging for people to deal with water properly due to certain of its physical characteristics. In light of this, object detection underwater has a wide range of uses, including environmental monitoring, surveillance, search and rescue, and navigation. This might enhance the precision, efficiency, and safety of undersea activities. In light of the aforementioned, this paper presents an algorithm for detecting objects underwater using YOLOv5. The algorithm has been improved by changing the way YOLOv5 works, which makes it better at detecting small objects. We tested our algorithm and found that it is more accurate than the original YOLOv5 algorithm.
IRJET, 2022
A systematic review of cybersecurity and
healthcare systems from the Artificial Intelligence (AI)... more A systematic review of cybersecurity and
healthcare systems from the Artificial Intelligence (AI) and
robotics perspective for the past 6 years is presented in this
research. Cybercriminals nowadays are always researching
new ways to break into corporate networks and steal sensitive
data. People frequently adhere to the same fundamental
security precautions on a daily basis, and as they use more
devices at work, for security experts, maintaining the data and
keeping them current is becoming more and more challenging.
AI in cybersecurity is gaining importance as it contributes to
overcoming the aforementioned difficulties. Additionally, the
advances brought about by AI and the field of robotics have
proved advantageous for the healthcare sector. With the use of
AI techniques like deep learning and machine learning, a
number of healthcare systems have been developed that
autonomously diagnose various diseases from medical images
and further generate reports based on the findings. This
research focuses on the role of AI and the field of robotics in
enhancing the cybersecurity and healthcare sector. The
research's literature demonstrates that AI in healthcare and
cybersecurity is still a new and innovative field that needs to
be studied further in the future. Researchers may utilize this
study to get helpful tips and knowledge for their next work.
International Research Journal of Engineering and Technology , 2023
A systematic review of cybersecurity and healthcare systems from the Artificial Intelligence (AI)... more A systematic review of cybersecurity and healthcare systems from the Artificial Intelligence (AI) and robotics perspective for the past 6 years is presented in this research. Cybercriminals nowadays are always researching new ways to break into corporate networks and steal sensitive data. People frequently adhere to the same fundamental security precautions on a daily basis, and as they use more devices at work, for security experts, maintaining the data and keeping them current is becoming more and more challenging. AI in cybersecurity is gaining importance as it contributes to overcoming the aforementioned difficulties. Additionally, the advances brought about by AI and the field of robotics have proved advantageous for the healthcare sector. With the use of AI techniques like deep learning and machine learning, a number of healthcare systems have been developed that autonomously diagnose various diseases from medical images and further generate reports based on the findings. This research focuses on the role of AI and the field of robotics in enhancing the cybersecurity and healthcare sector. The research's literature demonstrates that AI in healthcare and cybersecurity is still a new and innovative field that needs to be studied further in the future. Researchers may utilize this study to get helpful tips and knowledge for their next work.
IRJET , 2023
Intracranial tumors simply known as brain tumors have proven to be one of the pressing causes of ... more Intracranial tumors simply known as brain tumors have proven to be one of the pressing causes of human mortality globally. One of the most challenging responsibilities in medical image processing nowadays is the detection of brain malignancies. These tumor types are formed by a mass of aberrant cells, and the percentage of individuals diagnosed with brain cancer is growing in relation to the aging population, which is a global health concern. Early identification and diagnosis of brain disorders can have a significant impact on efforts to treat them. Given the aforementioned, deep learning approaches can assist notably in overcoming the above-stated challenges. In detecting and classifying brain/intracranial tumors from Medical Resonance (MR) images, which is one of the advanced methods in the field of medicine, we developed a deep learning model and deployed it to a web application that works using Convolutional Neural Networks (ConvNet) based on Transfer Learning (TL). This system is capable of identifying and distinguishing tumors among three major classes of brain tumors which are; Glioma, Meningioma, Pituitary, and normal images as well with very high accuracy.
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Papers by Usman Ibrahim Musa
healthcare systems from the Artificial Intelligence (AI) and
robotics perspective for the past 6 years is presented in this
research. Cybercriminals nowadays are always researching
new ways to break into corporate networks and steal sensitive
data. People frequently adhere to the same fundamental
security precautions on a daily basis, and as they use more
devices at work, for security experts, maintaining the data and
keeping them current is becoming more and more challenging.
AI in cybersecurity is gaining importance as it contributes to
overcoming the aforementioned difficulties. Additionally, the
advances brought about by AI and the field of robotics have
proved advantageous for the healthcare sector. With the use of
AI techniques like deep learning and machine learning, a
number of healthcare systems have been developed that
autonomously diagnose various diseases from medical images
and further generate reports based on the findings. This
research focuses on the role of AI and the field of robotics in
enhancing the cybersecurity and healthcare sector. The
research's literature demonstrates that AI in healthcare and
cybersecurity is still a new and innovative field that needs to
be studied further in the future. Researchers may utilize this
study to get helpful tips and knowledge for their next work.