Final Year Projects (FYPs) - Undergraduates

Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/37

This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.

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Author: search.filters.author.Dr. Zeeshan GillaniSubject: search.filters.subject.FA16

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    Terrific Traffic
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-11-20) Sarmad Khan; FA16-BCS-099; Dr. Zeeshan Gillani; LHR TP 6158
    The proposed is a system to detect traffic violations through anomalies detection using Machine Learning techniques from within a live traffic video stream. An anomaly is considered an irregularity or an event which would not occur in normal circumstances. Keeping traffic violations in account the circumstances will be such as Accidents, car crashes and lane violation. The proposed system will be able to differentiate not only between a normal and an abnormal event based on the events in the video stream but will also classify the anomaly accordingly. The purpose of this system is to automate and facilitate the traffic surveillance tasks in daily life. This result is achieved through implementing Image Processing and Deep learning techniques to predict the anomalous section of a video.
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    Crop Analytic Using Drone Imaging
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020) Shehroz Shafiq Khan; FA16-BCS-153; Dr. Zeeshan Gillani; LHR TP 6149
    The population around the globe is increasing at an alarming rate, which results in the food crisis in the following couple of decades. The use of advanced technologies such as remote sensing with the help of satellite or unmanned aerial vehicle (UAV) could be used to overcome this problem. Drone-based image techniques could be used for crop yield prediction, crop identification, water management, weather, and environmental factors could be observed. With the help of Convolutional neural network (CNN) based models, we can extract some important features from it, and with the help of those features, we can estimate our crop yield.
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