MS: Recent submissions

  • Deep Learning Based Supervised Classification of Water Bodies from High-Resolution Multispectral Sentinel-2 Imagery 
    Malik, Rafia (School of Electrical Engineering and Computer Science,(SEECS) NUST, 2021)
  • Applications of Low Dimensional Manifold Method in MRI and Depth Image Reconstruction 
    Abdullah, Saim (School of Electrical Engineering and Computer Science,(SEECS) NUST, 2020)
  • GENERATIVE AI FOR SIGNATURE SPOOFING 
    Amjad, Haadia (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)
    Biometric data reveals characteristics of human traits that are helpful for identifica tion and verification purposes. A handwritten signature is a type of biometric data that is widely used for online and offline ...
  • Information Extraction From Document Forms Using Deep Learning 
    Shehzad, Khurram (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)
    Information extraction from printed documents images remains an active re search area. Several methods have been proposed in literature that extract information by utilizing various approaches, e.g., using document ...
  • How Do People Look at Crowds? A Psychophysics Perspective. 
    Mehboob, Sobas (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)
    Crowds of people offer multitudes of stimuli for attracting gaze and attention. A crowded scene is considered to be formed with a small or a large number of objects or people standing together in a scene. What influences ...
  • Using Chest Scans for the Diagnosis of COVID-19 
    Muhammad, Reem Fida (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)
    COVID-19 is a viral infection that affects the human respiratory system. Since the victims of COVID-19 are increasing globally, this contagious disease is characterized as a pandemic by the World Health Organization ...
  • Informative Attention Based Deep Network For Person Re-Identification 
    Faizan, Rao (School of Electrical Engineering and Computer Science (SEECS), NUST, 2021)
    Person re-identification (ReID) is the most essential task in visual based surveillance. The recent success of deep learning in extracting unique and powerful discriminatory features has made immense shift in this era. ...
  • Application of deep learning for Urdu numeral recognition 
    Bhatti, Aamna (School of Electrical Engineering and Computer Science, (SEECS), NUST, 2021)
    Urdu is a complex language widely spoken in South East Asia. Since it is also the national language of Pakistan, Optical Character Recognition (OCR) finds much application of Urdu numerals in our country. In many areas, ...
  • Forensic Analysis Of Blackhole Attack in Wireless Sensor Networks 
    Hasan, Ahmad (School of Electrical Engineering & Computer Science (SEECS)-NUST, 2020)
    In recent years, Wireless Sensor Networks (WSN) has been exponentially proliferated in almost every domain of life encompassing civil and military sectors. In fact, due to the flexible implementation nature, WSN has become ...
  • Vehicular Traffic Flow Parameter Estimation Using Deep Neural Networks 
    RAEES, Muhammad (School of Electrical Engineering and Computer Science (SEECS), NUST, 2021)
    To overcome the challenges regarding the fixed place camera installation we introduce a drone based real time traffic flow parameter estimation. With the recent convenience of UAV (Unmanned aerial vehicles) videos begins ...
  • 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 ...

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