I am really new to Neural Networks and to Machine Learning in general, and I have been given a dataset composed by images for performing multi-class image classification with a CNN.
The images were already divided into classes, and looking at the images I have noticed that some of them are complitely different from the class they belong, for example If I have a class Fruits, with images of fruits, in the folder of this class I have some pictures of cars, people,..., which of course are not fruits and neither belong to any other class in the classification problem.
The problem is that this creates some problems when I train my CNN, and this results in a low accuracy, infact I cannot go above 0.5.
How do I deal with the fact that I have images which are not consistent with the class they belong?