I have uploaded images in the dataset on Roboflow project. As, I have a free account, I get to train a model only two times and this does not give me much of the accuracy. I am student working on my Final Year Project and I have no money to buy a premium version of Roboflow so that i could train my model on the images that i gave. What can I do ? Also I remember that i submitted an application for a student applying for more training versions, it was shown on their website as “Apply for Research Credits: Additional training credits and increased account limits are available for research and education. Academic institution email address required.”, but there is no reply. What should I do now?
I understand your situation. As a student, you can indeed apply for additional training credits and increased account limits for research and education purposes on Roboflow. This is mentioned in the Roboflow blog and in several forum posts (source 1, source 2, source 3).
If you have already applied for these additional credits and haven’t received a response yet, it might be due to the fact that there isn’t a set timeline for applying educational credits as mentioned in this forum post.
I would recommend reaching out to Roboflow’s support team directly through their forum or contact form to follow up on your application. Make sure to provide all the necessary details about your project and your academic institution, as this information helps them prioritize the process.
In the meantime, you can also consider using Roboflow’s open source notebooks with your own compute resources as suggested in this forum post. This might allow you to continue your work while waiting for a response from Roboflow.
Hi! I’m Roboflow’s AI powered bot. This is an automated response powered using AI with knowledge from our docs, blog, and forum. If this solves your issue, please mark it as the solution using the checkbox icon. If this doesn’t solve your issue, please follow up with what you’ve tried/why, and the community will continue to chime in as usual.
