Computer Science: Recent submissions

  • Abstractive Text Summarization of Judicial Cases in Supreme Court of Pakistan 
    Anwar, Muneeb Ahmed (School of Electrical Engineering and Computer Science (SEECS), NUST, 2021)
    Due to the large quantity of legal data availability on the internet, and other resources, it is vital for the research groups to carry broad research in the field of legal text processing, which can assist us make sense ...
  • Deep Learning Based Segmentation of 3D Point Clouds 
    Mehmood, Saba (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)
    3D models like point clouds are very widespread these days and are being used in numerous fields. Despite their broad availability, there is still a perti nent need of automatic approaches for semantic segmentation of ...
  • Tags Recommendation Based on Social Context 
    Riasat, Tuba (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)
    Social media platforms are not just a source of communicating with each other but also the main source of generating web content like images. Users upload the images along with the tags describing the content of the ...
  • Identifying Influential Factors Affecting Pregnancy Events Using Machine Learning Approaches 
    Tasneem, Aymen; (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)
    Despite of health awareness campaigns and improvements in education system, neonatal mortality is still a critical issue around the world. Out of 140 million children born annually, 4 million die in the first month of ...
  • Deep learning based human age estimation using inertial data of normal walk 
    Arshad, Khawaja Ali (2021)
    Human gait enables information about soft biometrics features in multiple scenarios where the environment and visual cues are not known. This characteristic of human gait has numerous application in the field of surveillance, ...
  • Tapping the power of multidimensional clinical data to identify Irritable Bowel Syndrome (IBS) endo-phenotype using Machine Learning 
    Khan, Uswah Ahmad (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)
    Irritable bowel syndrome (IBS) physiopathology is a complicated and multidimensional condition that continues to confound researchers and clinicians alike. Despite substan tial research, our understanding of the underlying ...
  • Urdu to English Neural Machine Translation using Transformers 
    Pervaz, Novera (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)
    Neural machine translation is a field of research that has gained worldwide interest over the years. It involves the use of deep learning algorithms to translate texts from one language to another. The research in this ...
  • Deep Learning Based OCR for Mathematical Expressions 
    Rehman, Asad (School of Electrical Engineering and Computer Sciences (SEECS), NUST., 2023)
    Mathematical expression recognition with the help of a deep neural network is proposed in this work. A latex sequence is generated from this model of a given mathematical expression image. An attention aggregation-base ...
  • An Efficient Hybrid Classification Model for Heart Disease Prediction 
    Munsif, Maaham (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Heart disease prediction is a critical task in healthcare, aiming to identify individuals at risk and enable timely intervention. In this study, we propose a novel approach that combines a genetic algorithm for feature ...
  • Multi dimensional data visualization for geographical data 
    Malik, Sara Imtiaz, (School of Electrical Engineering and Computer Science, 2018)
  • Towards a generic deep model: Human gait analysis using wearable devices for smart health care in internet of health things 
    Mehmood, Kiran (SEECS National University of Science & Technology, 2023)
    Human gait is a fascinating subject due to its unique bipedal nature, which encodes valuable information and patterns within its sparse kinematics. Previous research has demonstrated that low-level signals captured by ...
  • Safe Autonomous Driving in Rainy Weather Conditions using Deep Learning 
    Akram, Muhammad Junaid (SEECS National University of Science & Technology, 2023)
    Rainy weather conditions have a substantial impact on the efficiency of autonomous driving systems, disrupting their ability to perceive the surrounding environment accurately. It can cause distortion in the input of the ...
  • Crop Type Classification using Multi-temporal Satellite Imagery 
    Khan, Asim Hameed (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    With the increasing number of satellites, remote sensing data is becoming more af fordable. This gratuitously available satellite imagery may be used as source data to map Cultivated and Non-cultivated areas & crops types ...
  • Improving Extractive Summarization of Scholarly Documents using BERT and BiGRU 
    Bano, Sheher (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Extractive summarization involves selecting and condensing key information from a text document, while preserving the overall meaning and coherence of the original content. There are several extractive summarization ...
  • Deep learning for Temporal Analysis of Urban Air Quality Assessment 
    Amin, Arslan (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Air pollution is a significant environmental problem in many countries, partic ularly in developing nations such as Pakistan. Exposure to high levels of air pollutants has been linked to serious health issues, including ...
  • VISION BASED 3-D LOCALIZATION OF UAVS USING DEEP IMAGE MATCHING 
    Khurshid, Mansoor (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Drones and UAVs are used both professionally and privately and they rely heavily on onboard GPS, altimeter, survey meter along with other navigational equipment for completing their automated flight paths. These systems ...
  • Fall detection in assisted living using wearable sensors in the context of Internet of Health Things (IoHT) 
    Kiran, Samia (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Falling is one of the major health concerns faced by elderly people globally. Accurate and timely prediction or detection of falls could result in a significant reduction in injuries and associated costs. In this study, ...
  • Aspect-based Sarcasm Detection in COVID-19 Vaccination Tweets using Transformers-based Approaches 
    Kousar, Adila (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Sentiment analysis is the technique that analyzes our attitudes and emotions toward an entity. Sarcasm is a factor that can affect sentiment analysis and eventually results in factually incorrect results. Several sentimental ...
  • Online Recruitment Fraud (ORF) Detection using Deep Learning Approaches 
    Akram, Natasha (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    In the age of advanced technology, the internet has drastically transformed our lives in different ways. The traditional way to perform any activity has now been switched online. Therefore, seeking a job and hiring ...
  • Towards Large-scale Unsupervised Face Recognition in Videos 
    Khurshid, Atif (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)
    Video content is ubiquitous in the modern world and there is a growing need for au tomated methods to extract information from videos. Face-based person retrieval is a particularly interesting task in this domain which ...

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