M. Ahmed Bhimra
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M. Ahmed Bhimra is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
M. Ahmed Bhimra is a MS Thesis student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
Spatio-Temporal Analysis of Landuse-Landcover Change Using Satellite Imagery Thursday 28 Feb, 2019 at 10:00 am in Smart Room 9-105 SBASSE. Abstract We propose an approach to recognize large scale, rapid spatio-temporal analysis of satellite remote sensing data. This technique can be used to measure longitudinal changes and yearly changes. Most of the existing methods either…
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…
Numan is a senior PhD Student in Computer Vision & Graphics Lab (cvglab) at LUMS Syed Babar Ali School of Science and Engineering.
Research Associate | Full Stack Developer | Web Scraping and Automation Expert | Certified DL & ML Specialist Muhammad Muqsit Islam is a full-stack developer proficient in Web Development, Computer Vision, and Deep Learning. They are skilled in Django, Django Rest Framework, React, Flask, TensorFlow, Docker and other technologies, effectively bridging the gap between frontend…
Aamer Zaheer is a Ph.D. candidate in the Department of Computer Science, Lahore University of Management Sciences. Publications: ICCV2011, ECCV2012 or did it take a change in perspective and large porn tubeTips to get Success in World of Fashion Modeling The Fashion ED Hardy Hoodies for Glamorous Ladies lesbian porn a vibrant suburbthe…
Shehryar Malik, Muhammad Umair Haider*, Omer Iqbal, Murtaza Taj Abstract: Network pruning reduces the size of neural networks by removing (pruning) neurons such that the performance drop is minimal. Traditional pruning approaches focus on designing metrics to quantify the usefulness of a neuron which is often quite tedious and sub-optimal. More recent approaches have instead…