MS: Recent submissions

  • A Hybrid Machine Learning Technique for Short-Term Electric Load Forecasting for Residential Users 
    Nawaz, Muhammad Awais (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    With the advancement of technology, people’s reliance on energy is rapidly increasing. Calculating a country’s power consumption is one technique to estimate its productivity and rate of development . Recently, countries ...
  • Semantic Segmentation of 3D Point Clouds Using Deep Learning 
    Manzoor, Muhammad Hasnat (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Arguably, one of the deep learning’s greatest achievements is transfer learning. It is proven that if we use a rich source dataset to pre-train a network (ImageNet in 2D) and after we use a smaller target dataset to ...
  • Machine Learning based Short Term Electric Load Forecasting for Domestic Users 
    Niaz, Anum (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Pakistan is facing a lot of problems in generating the required amount of energy and supplying it to the people. Most of the utility companies use load forecasting to anticipate how much power they'll expect to fulfil ...
  • Quantifying Severity of Symptoms in Patients with Parkinson’s Disease Using Wearable Sensors and Machine Learning 
    Khan, Umar (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Parkinson’s disease has been an active area of research from a long time. Although no cure for it has been discovered yet, but certain medicines, surgical treatments, or other therapies can sometimes provide some relieve ...
  • Deep learning-based fall detection in Internet of Medical Things using wearable sensors 
    Shahid, Abdul Mannan (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Accidental and sudden fall is a significant cause of injury and even death in most cases, among the old age people. As it has a remarkable impact on the national health system, so extensive development and proper research ...
  • Crop Identification Using Remote Sensing Technology 
    Naqvi, Syed Manshoor Ali (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Crop identification and classification plays vital role in agricultural monitoring and use of resources efficiently to develop sustainable systems and provide high productivity. However, it remains a challenge to monitor ...
  • Deep Transformer-based Semantic Segmentation using Remote Sense Data 
    Farhat Ul Ain, Syeda (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Semantic segmentation is an important job in computer vision, and its applications have grown in popularity over the last decade. When we talk about remote sense imaging, different aspects are there which proved to be ...
  • Semantic Segmentation of 3D Point Clouds using Deep Learning 
    Muhammad Umair Waheed, Rao (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    This thesis presents a new fine-grained analysis on large-scale point cloud semantic segmentation through a mechanism which fuses a local and global context aware feature representation strategy into a semantic ...
  • Test Suite Reduction Using K-means Clustering 
    Saleem, Jabran (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Regression testing involves re-execution of test suite whenever a software undergoes any update. This cost is increased manifolds due to recent continuous integration practices in software industry. There are many ...
  • Translytics - A new approach for runtime selection of database layout based on user’s context 
    Tanvir, Muhammad Makhshif (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Currently organizations have to maintain the separate systems for transactions and analytics inside the company. Notably, different vendors provide the capabilities for either of these tasks and this requires specialized ...
  • Investigating Mempool Optimizations for Ethereum 
    Arshid, Syeda Roushan (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    In this paper, we propose a new scheme OMCEM that optimizes the memory consumption of the Ethereum mempool. Our work will be as follows: at first, we Transform Ethereum mempool to a bloom filter based scheme with some ...
  • Multilingual Traffic Signboard Detection & Recognition in Natural Scene Images 
    Butt, Muhammad Atif (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Numerous text detection and recognition methods have been proposed in recent times that have demonstrated remarkable performance on the standard benchmark datasets. The existing datasets includes the scripts of numerous ...
  • Multimodal Knowledge Reasoning for Enhanced Visual Question Answering 
    Hussain, Afzaal (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Visual Question Answering (VQA) is a multidisciplinary task in the field of Natural Language Processing (NLP) and Computer Vision (CV) in which an image and a ques tion are given to a VQA system which is responsible to ...
  • Chest X-ray Abnormalities Detection using Deep learning 
    Irfan, Yasir (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Thorax illness is a serious medical problem. Approximately 3 million individuals die each year from thoracic disorders, according to a recent report [10]. Inspection of medical images demands strong degree of professional ...
  • Improving the performance of Pakistan’s judicial system and its ranking using data analytics 
    Mehmood, Faisal (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    A large number of lawsuits are pending with various courts in Pakistan. This large num ber of pending lawsuits indicates the ineffectiveness of the justice system. An ineffective justice system contributes to decreasing ...
  • Predicting soft biometrics of a human by using gait signatures 
    Munir, Omair (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Human walking pattern is believed to be unique in its nature and it is well-known through a number of previous research that soft biometrics of humans are encoded in sparse kinematic information, or in other words, in ...
  • Towards efficient resource utilization in collaborative fog environment using multi-armed band 
    Saleem, Rabia (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    I am thankful to my Creator Allah Subhana-Watala to have guided me throughout this work at every step and for every new thought which You set up in my mind to improve it. Indeed, I could have done nothing without Your ...
  • Machine Learning based Predictive Maintenance Framework for an Industrial Internet of Things 
    Ilyas, Tuba (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    First, I would like to express my gratitude to Allah Almighty (SWT) for his abundant blessings. After that, I am sincerely grateful to my supervisor for his priceless guidance, encouragements, devotion, and patience. ...
  • SECURING NETWORKS USING SOFTWARE DEFINED NETWORKS AND MACHINE LEARNING 
    Mughal, Fazeela (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Machine Learning techniques are used in Networks to detect DoS and DDoS attacks and to resolves network security issues. As many researchers done their research either on real time datasets or synthetic datasets on ...
  • Non-Intrusive Load Monitoring (NILM) using a LSTM with socio-economic parameters 
    Taimoor, Ahmed (SEECS-School of Electrical Engineering and Computer Science NUST Islamabad, 2022)
    Nonintrusive load monitoring (NILM) deconstructs aggregated electrical us age data into individual appliances. The dissemination of disaggregated data to customers raises consumer awareness and encourages them to save ...

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