“…In various machine learning applications, using transfer learning for feature extraction is an effective technique [ [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] ]. This technique involves using a pre-trained model to extract meaningful features from the input images, which can improve the model's generalization ability and reduce the risk of over-fitting [ 47 , 48 ].…”