International AI-based Dhaka Traffic Detection Challenge
The capital city of Dhaka has only 7% traffic roads (compared to 25% urban standard) in presence of approximately 8 million commuters a day within 306 sq km area. The scenario of Dhaka traffic is unique which poses complex new challenges in terms of automated traffic detection. To solve the problem using advances in AI-based technology and ICT solutions, we are calling for solutions to automatic Dhaka traffic detection problems on optical images.
This new AI-Based Dhaka Traffic Detection Challenge aims at assessing the ability of state-of-the-art methods to detect and recognize traffic vehicles. This solution is encountered in modern cities where multiple cultures live and communicate together, where users see various scripts and languages in a way that prevents using much a priori knowledge. Also, at the same time, academics and researchers from the region who are experts in AI or interested in exploring possibilities could be brought to a networking community through this campaign. Working together on a common problem statement can create the right synergies needed to build an AI-based community in South-East Asia.
What is this challenge?
The competition will happen online and within 2 rounds. In the first round, a training dataset would be provided with which the participants need to train a generalized object detection model to locate traffic vehicles and identify them on the 1st test dataset and generate a submission file following the prescribed format. Based only on the detection accuracy, the top 30% team will move to the 2nd round where they will be evaluated based on the detection accuracy on the 2nd test dataset, poster, presentation, and codes.
Participation fee: Free for all (maximum 5 persons per team)
Prizes and Awards:
The winning team gets a prize of 1,00,000 BDT
STI 2020 conference participation (virtual) for top 10 teams http://fse.green.edu.bd/sti-2020/
How to participate?
There can be 1-5 members in a team. A person can not be in more than one team.
Once registered, you can not change your team or any information provided. So, be sure before your registration
Download the training datasets and adapt your method(s) to input/output file formats
Run your method on the test dataset and submit the results
You can submit your dataset maximum 5 times a day. Incorrect submissions (accuracy = -1) won't be counted.
*Please remember to cite the dataset if you use it for any future publications*