Every challenge participant agrees to use the provided data only in the scope of the DATA USE AND CONFIDENTIALITY AGREEMENT for access to data.
Every challenge participant agrees not to make more than one account for downloading data and submitting the
results.
After
the release of the validation dataset, challenge participants may upload
output results of their learning models as described in the
submission guidelines of the challenge before the deadline including a
summary of their own learning model. By submitting the participant’s
results, every challenge participant confirms that their work is original
and only includes material that they own or have permission from the
rightful owner to use
By submitting the results to this challenge,
participants understand and agree to include those results for the method
comparison. This comparison will be used to prepare a joint publication in
which the writing process will be led by the challenge organizer(s). First
and last authorship position will correspond to the challenge
organizer(s), and each participating team will have at least one
contributing co-author in the author list.
Every challenge member agrees that the decisions of the challenge committee will be final and binding all matters related to this challenge. If there is any change to data, schedule, instructions of participation, or these rules, the registered participants will be notified to the email addresses
they provided when they are registered.
If an unforeseen or unexpected event (including, but not limited to: someone cheating; a virus, bug, or catastrophic event corrupting data or the submission platform; someone discovering a flaw in the data or modalities of the challenge) that cannot be reasonably anticipated or controlled, (also referred to as force majeure) affects the fairness and/or integrity of this challenge, the committee reserve the right to cancel, change or suspend this challenge. This right is reserved whether the event is due to human or technical error.
Computer “hacking” is unlawful. If any participant attempts to compromise the integrity or the legitimate operation of the challenge by hacking or by cheating or committing fraud in any way, the committee may seek damages from him/her to the fullest extent permitted by law.
For training the network, no external
data is allowed except the official dataset provided in this challenge and pre-trained models using the ImageNet database such as VGG16, InceptionV3, ResNet, etc.
Prizes
TBD
Publication
High ranked teams will be suggested to submit papers to Health Informatics Research (HIR, www.e-hir.org) which is a SCOPUS citation journal. The submission is optional, but the HIR journal will provide a fast track review.
