Rajtar, JakubSzajerman, Dominik2023-09-212023-09-212023Rajtar J., Szajerman D., Weak Supervision in Enemy Detection Based on Computer Game Output Video Stream. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 80-86, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.11.978-83-66741-92-8http://hdl.handle.net/11652/4786https://doi.org/10.34658/9788366741928.11This work contains a solution for image classification and enemy detection in the output video stream of a computer game. Weak supervision was used to achieve the goal. It shows that an image dataset with a certain number of incorrect classification labels can be used to correctly build a classification model that distinguishes between images containing and not containing an enemy. Based on the results of such classification stage and the use of class activation maps, a method for detecting enemies on positively classified images was proposed. The tedious process of image labeling, which is necessary for supervised learning, does not occur here.enDla wszystkich w zakresie dozwolonego użytkuFair use conditioncomputer game testingcomputer visionweak supervisiontestowanie gier komputerowychwizja komputerowasłaby nadzórRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.11