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Deep Learning

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Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc. In this course we…

ICASSP 2019 – Using 3D Residual Network For Spatio-Temporal Analysis Of Remote Sensing Data
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ICASSP 2019 – Using 3D Residual Network For Spatio-Temporal Analysis Of Remote Sensing Data

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Muhammad Ahmed Bhimra, Usman Nazir, Murtaza Taj International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, May 12-17, 2019 Abstract In this paper, we propose an approach to recognize spatio-temporal changes from remote sensing data. Instead of performing independent analysis on each instance of satellite imagery, we proposed a 3D Convolutional Neural Network…

Murtaza Taj
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Murtaza Taj

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Murtaza Taj earned his Ph.D. and M.Sc. degrees in electronic engineering and computer science from the Queen Mary University of London (QMUL), United Kingdom, in 2009 and 2005, respectively. Currently, he is an Associate Professor at the Lahore University of Management Sciences (LUMS), Syed Babar Ali School of Science and Engineering, Pakistan. He also served as…

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Summer Internships 2019

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Content Based Image Retrieval Using Hand Crafted Features Asim Waheed, Khawaja Umair Ul Hassan The project involved solving the Cross-View image matching problem between Satellite view images and Street view images. Many hand-crafted features were calculated, such as Histogram, HOG, Bag of Visual Words and VLAD using SIFT and SURF descriptors. The compiled features would…

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