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
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
Our NRPU proposal on “Analyzing and Forecasting Socio-economic development using Satellite Imagery of Districts of Punjab” has been approved for funding by HEC. Acceptance rate among CS & IT related proposals in NRPU call for 2017-18 was only 3% and the overall acceptance rate was only 28%. Our is amongĀ 1104 accepted proposals out of total…
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,…
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…
The Computer Vision Lab hosted a rigorous summer internship program for undergraduate students. Sophomore, Junior and Senior interns worked for 2 months in the lab, under the supervision of faculty and PhD students. The students worked both individually and in groups, on a range of ideas, from making a campus 3D model to automatic generation…
Challenging the dogma of Relevance Feedback in Content based Image Retrieval Systems with Deep Learning May, 2018 at 3:00 pm in Smart Room 9-105 SBASSE. Abstract Association of images to their content based similar images in a database, is quite a fascinating challenge specially on social media platform where billions of tagged and untagged images…