Paper accepted at ICASSP 2022
Our paper titled “Camera Calibration through Camera Projection Loss” accepted at ICASSP 2022.
This work was an outcome of MS Thesis by Talha Hanif Butt
More info: Click here
Our paper titled “Camera Calibration through Camera Projection Loss” accepted at ICASSP 2022.
This work was an outcome of MS Thesis by Talha Hanif Butt
More info: Click here
Arif Mahmood successfully defended his Ph.D. thesis on May 27, 2011 at LUMS, Lahore. Thesis Abstract: Template matching is frequently used in Digital Image Processing, Machine Vision, Remote Sensing and Pattern Recognition, and a large number of template matching algorithms have been proposed in literature. The performance of these algorithms may be evaluated from the…
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…
PhD (Stipend, Fees) 2 x PhD Position in Agriculture Robotics, Machine Learning, Computer Vision 2 x PhD Position in Satellite Imagery, Deep Learning, Image Processing MS (Stipend) 2 x MS Position in Agriculture Robotics, Machine Learning, Computer Vision 2 x MS Position in Satellite Imagery, Deep Learning, Image Processing How To Apply: Email: murtaza.taj@lums.edu.pk Apply Online: https://admissions.lums.edu.pk/
Our paper titled “Teacher-Class Network: A Neural Network Compression Mechanism” accepted at BMVC 2021. This work was an outcome of MS Thesis by Shaiq Munir More info: Click here
Two of our papers accepted at ICIP 2021 1. “Spatio-Temporal Crop Classification On Volumetric Data”, More info: Click here 2. “Comprehensive Online Network Pruning via Learnable Scaling Factors”, More info: Click here
Tuesday 20 Nov, 2012 at 5:50 pm in Smart Room 9-105 SSE. Abstract A variety of dynamic objects, such as faces, bodies, and cloth, are represented in computer vision and computer graphics as a collection of moving spatial landmarks. A number of tasks are performed on this type of data such as character animation, motion…