Computer Science: Recent submissions

  • Estimation of Geo-Location of an Image Using Affective Image Classification 
    Khan, Muhammad Bilal (School of Electrical Engineering and Computer Science (SEECS), NUST, 2018)
    Images have always been affecting viewers on an emotional level by portraying so much in a single frame. These emotions have been involved in human decision making. Machines can also be made emotionally intelligent using ...
  • A Cloud Based Disease Surveillance and Health Information System 
    Bashir, Adnan (School of Electrical Engineering and Computer Science, (SEECS), NUST, 2018)
    Outbreaks can overwhelm weak or fragile health systems that lack the tools, infrastructure, policies, and systems to keep communities healthy and safe. Timely detection, preparedness, and appropriate response are essential ...
  • Incremental Learning of Object Detectors using Limited Training Data 
    Hafeez, Muhammad Abdullah (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)
    State of the art Deep learning models, despite being at par to human level in some of the challenging tasks, still suffer badly when they are put in the condition where they have to learn with the passage of time. This ...
  • Incorporating Big Data Aspects In Incremental Taxonomy Evolution 
    Aalijah, Kanwal (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)
    Big data is a breakthrough technology that has been developed over the years. Big data means very large set of data that grows in ever increasing rate and the volume of data is of size Exabyte (1018). It refers to ...
  • Runway Detection and Localization in Aerial Images for UAV Landing using Deep Learning 
    Akbar, Javeria (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)
    Landing is the most difficult phase of flight for a drone. Due to lack of efficient systems, there has been numerous accidents resulting in damaged hardware. Vision based systems have been proved significantly popular ...
  • Machine Learning based Prediction and Evaluation of COVID-19 Patient’s Symptoms Data from Rawalpindi and AJK, Pakistan Region. 
    Wahid, Hajira (School of Electrical Engineering and Computer Science (SEECS), NUST, 2022)
    COVID-19 was discovered to be an infectious and potentially fatal viral disease, and its quick and extensive spread has turned it into one of the world’s most critical problems. People across the globe were facing an ...
  • REGION AND TIME WISE TWITTER BASED PCR ANALYSIS: A COMPARATIVE RESEARCH ON PEOPLE’S SERIOUSNESS TOWARDS COVID-19 
    Raz, Ghulam Musa (School of Electrical Engineering & Computer Science (SEECS), NUST, 2021)
    As we all are living in pandemic covid19, which is affecting every perspective of daily life. Every class is badly suffering from this disease. It has been a subject of discussion since 2019 due to the increased ...
  • Object Recognition and Segmentation using unstructured 3D Point Clouds 
    Sheikh, Mehak (School of Electrical Engineering and computer Science (SEECS), NUST, 2019)
    Point Clouds are an imminent source of the scalable geometric data structure. They are widely used in computer graphics or computer graphic applications. Point clouds are in unstructured form, due to irregularities in ...
  • Crop Monitoring via Remote Sensing 
    Iqbal, Zubair (School of Electrical Engineering and computer Science (SEECS), NUST, 2021)
    The increasing world population is generating higher food demand that needs effective cultivation methodologies to meet them, especially for the developing countries that have a higher dependence on the agricultural ...
  • Adversarial Attacks and Defenses using transform domain techniques 
    Maryam (School of Electrical Engineering and computer Science (SEECS), NUST, 2023)
    Deep neural networks (DNNs) have shown impressive performance on a diverse set of visual tasks, when deployed in real-world environments. The study reveals that even state-of-the-art neural networks are susceptible to ...
  • 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 ...

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