MS: Recent submissions

  • Using machine learning techniques for censorship-resistant communication 
    Huma, Zil e (School of Electrical Engineering and computer Science (SEECS), NUST, 2021)
    To prevent citizens from accessing unfiltered information over the internet, repressive governments usually deploy national level censorship. To counter these censors, a number of systems have been introduced that make ...
  • Agent-based Modeling and Simulation of Household Electricity Demand Profiles 
    Ain, Quair tul (School of Electrical Engineering and computer Science (SEECS), NUST, 2019)
    In Pakistan, there is shortage of electricity generation. As per Pakistan National Transmission & Dispatch Company (NTDC); Pakistan will be able to meet the projected demand of peak hours in 2019. In Pakistan, the major ...
  • Sector-wise Investigation of Bring Your Own Device (BYOD) Security Policies in Pakistan 
    Sajid, Ayesha (School of Electrical Engineering and computer Science (SEECS), NUST, 2021)
    With the advancement in technology and pervasiveness of computing devices, new practices have been adopted by various organizations to optimize their infrastructure and to efficiently utilize the available resources and ...
  • Information Extraction from Tables in Document Images using Deep Learning 
    Shahzad, Muhammad Ali (School of Electrical Engineering and computer Science (SEECS), NUST, 2019)
    features for tasks such as visual object detection. The recent success of deep learning in automatically extracting representative and powerful features from images has brought a paradigm shift in this area. As a side ...
  • Segmentation and Classification of 3D Point Clouds Using Deep Pointwise Residual Networks 
    Arshad, Saira (School of Electrical Engineering and computer Science (SEECS), NUST, 2019)
    Deep learning in computer vision domain plays an important role in the last few years. Its performance surpasses previous approaches based on handcrafted features. Deep learning based approaches yield better performance in ...
  • Automatic COVID-19 Detection using Deep Features 
    Khan, Muhammad Yasir Ali (School of Electrical Engineering and computer Science (SEECS), NUST, 2021)
    The disease named Coronavirus (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2), first appeared in Wuhan city of China in late 2019, spread globally, infected millions with high mortality ...
  • Enhancing Intrusion Detection: Leveraging Federated Learning and Hybrid Deep Learning Models 
    Naeem, Faiza (School of Electrical Engineering and computer Science (SEECS), NUST, 2023)
    An efficient and productive IoT application may ease some real-time tasks however, it is at risk of cyber-attack. Intrusion Detection Systems (IDS) are of significant importance for the security measures of IoT applications. ...
  • Monitoring and Quantification of Parkinson’s Disease Motor Symptoms using Wearable Sensors for Smart Healthcare 
    Sarwar, Muhammad Ali (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)
    Research on Parkinson’s disease has been ongoing for a while. Since there is now no known treatment for it, there are occasionally some symptoms that can be relieved with particular medications, surgical procedures, or ...
  • Intelligent Assistive Evaluation System for English Comprehension Skills 
    Rasheed, Maha (School of Electrical Engineering and computer Science (SEECS), NUST, 2021)
    Student comprehension has many metrics as well as categories in which it is measured. Assessment of comprehension skills of the English language in young children is a human-resource-heavy task. It requires an ample amount ...
  • Patent Semantic Annotation for Practitioners 
    Kabir, Summiya (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)
    Having a patent document, associating discrete semantic annotations has emerged as an exciting research area. Text annotation aids patent practitioners, such as; examiners and attorneys in quickly identifying the important ...
  • An Optimized Cancer Classification Approach Using Deep Learning 
    Iqbal, Sidra (School of Electrical Engineering and computer Science (SEECS), NUST, 2023)
    Cancer, being a genetic disease, is engendered when the body’s cells grow uncontrollably and disseminate to other parts of the body. Early diagnosis and classification of cancer predominantly focus on recognizing symptomatic ...
  • Self Supervised Crop Type Classification using MultiSpectral Remote Sensing 
    Fatima, Syeda Faizan (School of Electrical Engineering and Computer Science (SEECS), NUST, 2023)
    Accurate and efficient crop classification using multispectral remotely sensed data is essential for crop yield estimation and agricultural management. However, one of the major challenges in this task is the limited ...
  • Deep Multi-Labelling based Unsupervised Person Re-Identification 
    Zarmeena (School of Electrical Engineering and Computer Science NUST SEECS, 2021)
    Person re-identification is the problem of finding the given person in the nonoverlapping cameras at a given time or finding the person that has appeared in the same camera but at different time stamps. The re-identification ...
  • Estimating Water Quality using Internet of Things and Machine Learning 
    Ahmed, Umair (School of Electrical Engineering and Computer Science NUST SEECS, 2019)
    Quality of water plays an important role in all aspects of our lives and it has been deteriorating at an alarming rate due to pollution, deeming its quick, inexpensive and accurate detection vital. Conventional methods ...
  • Localization of abnormalities in EEG signal 
    Faisal, Tayyaba (School of Electrical Engineering and Computer Science NUST SEECS, 2021)
    Electroencephalogram (EEG) can be used for the diagnosis of neurologist disorders: Alzheimer’s disease, depression, dementia, and epilepsy. Manual interpretation of EEG is time consuming and resource hungry process. ...
  • Air-Flow Analysis in Smart Buildings using Fuzzy Logic 
    Naqvi, Syed Furqan Haider (School of Electrical Engineering and Computer Science NUST SEECS, 2019)
    Building energy management is an emerging area of research with a wide variety of techniques applied in it. During the past few years, there is a huge rise in the demand for energy due to the exponential growth of ...
  • Locality aware distributed processes scheduling to improve efficiency using machine learning techniques 
    Zaheer, Saad (School of Electrical Engineering and Computer Science NUST SEECS, 2018)
    Cloud provides a shared computing space on a pay-as-you-go model. Due to this sharing, it is difficult to execute the task efficiently in terms of time. Several factors play its parts such as process scheduling and ...
  • Multi Modeling Approach for Effective Water Resource Management in NUST 
    Ali, Romana (School of Electrical Engineering and Computer Science NUST SEECS, 2020)
    Freshwater is the naturally occurring water on earth except for brackish water and seawater. Water Scarcity has affected freshwater resources of all the countries including Pakistan and has become one of the largest ...
  • Large Scale Fine-Grained Visual Recognition 
    Usman, Omer (School of Electrical Engineering and Computer Science NUST SEECS, 2021)
    Computer Vision depends on pattern recognition techniques to self-train and understand visual data. While machine learning algorithms were previously used for computer vision applications, now deep learning methods ...
  • Orientation Aware Weapons Detection in Visual Data 
    Haq, Nazeef Ul (School of Electrical Engineering and Computer Science NUST SEECS, 2020)
    Automatic detection of weapons is significant for improving security and well being of individuals, nonetheless, it is a difficult task due to large variety of size, shape and appearance of weapons. View point variations ...

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