Paper accepted at ICONIP 2023
Our paper titled “Stereoential Net: Deep Network for Learning Building Height Using Stereo Imagery” accepted at ICONIP 2023.
This work was an outcome of PhD Thesis by Sana Jabbar
More info: Click here
Our paper titled “Stereoential Net: Deep Network for Learning Building Height Using Stereo Imagery” accepted at ICONIP 2023.
This work was an outcome of PhD Thesis by Sana Jabbar
More info: Click here
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
“Using 3D Residual Network For Spatio-Temporal Analysis Of Remote Sensing Data”, “Adaptively Weighted Multi-Task Learning Using Inverse Validation Loss” and “Point Cloud Segmentation Using Hierarchical Tree for Architectural Models” have been accepted in “IEEE International Conference on Acoustic Speech and Signal Processing. This conference is going to be held from 12th to 17th May 2019…
Learning Socio-economic Indicators from Remote Sensing Data Thursday 12 Sep, 2019 at 03:30 am in CS Smart Room 9-105 SBASSE. Abstract Progress on the UN Sustainable Development Goals (SDGs) is hampered by a persistent lack of data regarding key social, environmental, and economic indicators, particularly in developing countries. For example, data on poverty and slavery,…
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…
Our paper titled “An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model: Combining automated radiological analysis with clinical and biomarkers data” accepted at Journal of Medical Primatology. This work was an outcome of work by Faisal Yaseen More info: Click here
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…