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In this challenge you will compete to develop the best automatic animal classifier. You will be provided with training data (labelled aerial images) and you will have to develop an automatic image classification system. You can leverage existing artificial intelligence/computer vision libraries and frameworks such as Caffe, OpenCV and Theano. Your task is to train a suitable algorithm to classify aerial images with a high accuracy.
|Expected results||Classification algorithm to classify animals.|
|Technical Information||The participant needs to bring a laptop and requires basic object oriented programming skills.|
Below is the evaluation criteria that will be used by the jury to select the winner(s) of the challenge.
|Evaluation Criteria||At the end of the challenge your algorithm is evaluated based on two metrics, namely, the overall average top 1 error and the overall average top 5 error.If your algorithm performs the best you will win a mini drone. Evaluation Criterion: We evaluate the performance of your classification algorithm on a separate ground truth dataset based on the two metrics the overall average top 1 error and the overall average top 5 error."|
|Process||Short introduction Development of algorithms with support of Birds.ai staff Evaluation Winner announcement|
|Jury||Anouk Visser & Camiel R. Verschoor.|
- Win a mini drone by developing your own automatic animal classifier. - 0.00 €