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Generative Adversarial Networks as a Method to Predict Stresses in Structures
(Mechanical Engineering, 2021 , Master Thesis)
There have been continuous advances in the field of Finite Element Analysis (FEA) allowing designers, architects, engineers and the public at large increasing ease and access. The methods of implementation however, have ...
USING CONTEXT SPECIFIC GENERATIVE ADVERSARIAL NETWORKS FOR AUDIO DATA COMPLETION: MUSICAL INSTRUMENTS CASE STUDY
(Computing, 2023 , Master Thesis)
Audio quality plays an essential role in several applications ranging from music to voice conversations. Sound information is subject to quality loss caused by reasons such as intermittent network connections, or storage ...