Tariq, Muhammad Umer(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
Acquiring comprehensive and varied datasets for training Machine Learning (ML) models
poses a significant worldwide challenge, especially in areas that need intricate data,
such as detecting plant diseases. This thesis ...
Khan, Reeha(School of Electrical Engineering and Computer Science, (SEECS)NUST, 2025)
Cephalometric analysis is a cornerstone of modern orthodontics, enabling precise diagnosis and
treatment planning by identifying key morphometric landmarks. Since manual identification of
these landmarks is labor-intensive ...
Zulfiqar, Anam(School of Electrical Engineering and Computer Science, (SEECS)NUST, 2025)
The following thesis presents the research to promote generalizability and explain
ability across multiple drug-disease contexts to integrate transfer learning into a re
inforcement learning framework. To address and ...
Bukhari, Syed Ali Haider(School of Electrical Engineering & Computer Sciences (SEECS), NUST, 2025)
When training an agent for either path planning or Simultaneous Localization and Mapping
(SLAM), datasets that include various scenarios according to the agent’s physical limitations are
required. Although there are a ...
Urooba, Syeda(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
Federated Learning (FL) is a collaborative learning platform. It enables users to train machine
learning models on their devices using their data. However, the final updated model they receive is trained on other datasets ...
Khurram, Muhammad(School of Electrical Engineering and Computer Science (SEECS)NUST, 2025)
In this modern era, Militaries are equipped with advanced communication equipment’s to conduct the intense communication activities by using satellite radio, antennas, Global Positioning System ‘GPS’, handheld sets, Inmarsat, ...
Abbas, Syed Zain(School of Electrical Engineering and Computer Science, (SEECS)NUST, 2024)
As vehicular networks increasingly rely on real-time applications such as autonomous
driving and intelligent transportation systems (ITS), Mobile Edge Computing (MEC)
has emerged as a crucial technology for reducing ...
Munir, Muhammad Ali(School of Electrical Engineering and Computer Science, (SEECS)NUST, 2025)
Deforestation is one of the most challenging issue that we are dealing with
as of today. The effects of complete deforestation have started to show up
so now governments and authorities have started to take firm measures ...
Rehan, Muhammad(School of Electrical Engineering and Computer Science (SEECS-NUST), 2024)
Image matching is one of many fundamental tasks in computer vision with a wide
range of applications, including image registration, camera pose estimation and 3D
reconstruction. Traditional image matching techniques ...
Gull, Muqaddas(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
Modern computer vision tasks rely heavily on extensive training data for accurate classification.
However, the collection and annotation of such data can be impractical.
To address this challenge, zero-shot learning (ZSL) ...
Ashfaq, Kiran(School of Electrical Engineering and Computer Science (SEECS)NUST, 2025)
Metasurfaces are artificially engineered structures that are proposed to employ the phase, amplitude, and polarization of the electromagnetic (EM) wave. Among many properties, polarization conversion of the EM wave is the ...
Khan, Fazal Muhammad Ali(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
Federated learning (FL) is a powerful, privacy-preserving machine learning (ML) technique
that trains models across edge devices without centralizing data, ensuring enhanced privacy
and optimizing bandwidth. Over-the-air ...
Shahzad, Khuram(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
In the modern era of rapid urbanization and pressing environmental concerns, the concept
of smart grids has emerged as a pivotal solution towards sustainable and energyefficient
cities. To fully leverage the capabilities ...
Usmani, Fehmida(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
In recent decades, optical transmission systems have undergone a revolutionary trans formation, driven by the surging demands of global internet traffic and bandwidth intensive applications. Technologies like software-defined ...
Mati Ur Rahman, Hafiz(School of Electrical Engineering & Computer Science (SEECS),NUST, 2024)
In an era marked by the relentless demand for enhanced networking solutions, this research
delves into the realm of Software Defined Optical Networks (SDON). Harnessing
the transformative power of Software Defined ...
Basharat, Sarah(School of Electrical Engineering and Computer Science (SEECS),NUST, 2024)
Reconfigurable intelligent surfaces (RISs), with the potential to realize smart radio
environments (SREs), have emerged as an energy-efficient and a cost-effective technology
to support the services and demands foreseen ...
Khan, Waqas Ali(School of Electrical Engineering and Computer Science (SEECS)NUST, 2025)
Inter-area oscillations provide a considerable risk to the stability of interconnected
power networks, as they involve generators from many regions, potentially resulting
in intensified oscillations in tie-lines. The ...
Mughees, Abdullah(School of Electrical Engineering and Computer Science (SEECS)NUST, 2024)
Unmanned aerial vehicles (UAVs), particularly quadcopters, have witnessed remarkable advancements,
showcasing their capabilities in diverse tasks and object manipulation. These advancements
are attributed to sophisticated ...
Khalid, Muhammad Abdullah(School of Electrical Engineering and Computer Science (SEECS) NUST, 2024)
In robotics, simulations are crucial, especially during the testing stage. However, the
sim2real gap remains a concern. For example, object segmentation learned on simulators
may not translate well on real world data ...