To develop a system that is able to quantitatively monitor forests of Pakistan by deploying a small low-cost UAV to acquire temporal images and possibly fuse it with available satellite imagery to enable thorough assessments of local forest conditions e.g., degradation and deforestation caused by theft, urbanization or natural factors Read more…
This research work aimed at automating paper-based mailbox of large companies by developing an automated document understanding system. To make this process efficient, the system was developed incrementally in order to extract the information from scanned documents.
To develop a machine learning software that can extract all the relevant data from a sample form (PDF) under the following assumptions There will be only one type of form that will be processed.Up to three variations of this form will be considered.Approx 100+ samples will be provided by client Read more…
In order to manage Pakistan’s water resources, it is necessary to enforce an even distribution of water throughout the year. WASABI is designed to predict flooding beforehand, supervise the volume of water bodies (including rivers, lakes, and reservoirs like dams, etc.), and predict the ratio at which the water level Read more…
To generate a crop monitoring system that enables the user to assess the crop’s phenological growth stages and based on extracted crop parameters, predict the crop yield productions. The developed system is intended to assist in filling gaps in policy makers information that is essential in ensuring sustainable management of Read more…
To employ underwater computer vision technology for an automated surveying of fish species. The project will form the basis for a non-invasive, low-cost surveying of Pakistan’s fish population, and benefit the preservation of endangered species as well as a more sustainable economic exploitation of Pakistan’s resources.
The goal of the proposed project is to employ underwater computer vision technology for an automated surveying of fish species by providing state-of-the-art automatic, non-destructive, cost-effective, and reliable solution. It will be able to detect and classify the available species of fresh water fish and a database of the fish Read more…
The project aimed to perform OCR on an extensive dataset of printed and handwritten Urdu documents. The computational power of the GPU, managed by TensorFlow, enabled us to perform extensive research on training uni or multi-directional LSTM in order to successfully develop an OCR of complex-script documents.