A method for determining process limits for one or more parameters of a semiconductor process, the method comprising the steps of: - providing one or more test substrates comprising a plurality of die areas, - applying the process on different die areas of the one or more test substrates, wherein the one or more process parameters are incremented, starting from a set value of the parameters at one of the die areas, and increasing and/or decreasing the parameter or parameters stepwise in the other die areas, - obtaining a dataset of images (3a,3b,3c) of the same portion of the different die areas, processed by applying different parameter values, - determining the process limits by a sequence of method steps comprising: creating a latent vector space by training an unsupervised generative machine learning algorithm on the basis of one or more of the images of the dataset, - selecting one or more query images from the image dataset, - for each query image, determining the distances in the latent vector space from the query image to a plurality of images from the dataset, the latter plurality of images being referred to hereafter as object images, - attributing a score to each of said object images, based on the distances between said plurality of object images and the one or more query images, wherein the query images, the object images and the definition of the score are chosen in such a manner that the score is representative of the one or more characteristics of the images, at least in a given range of said one or more characteristics, - extracting the process limits from the relation between the score and the one or more process parameters. - providing one or more test substrates comprising a plurality of die areas, - applying the process on different die areas of the one or more test substrates, wherein the one or more process parameters are incremented, starting from a set value of the parameters at one of the die areas, and increasing and/or decreasing the parameter or parameters stepwise in the other die areas, - obtaining a dataset of images (3a,3b,3c) of the same portion of the different die areas, processed by applying different parameter values, - determining the process limits by a sequence of method steps comprising: creating a latent vector space by training an unsupervised generative machine learning algorithm on the basis of one or more of the images of the dataset, - selecting one or more query images from the image dataset, - for each query image, determining the distances in the latent vector space from the query image to a plurality of images from the dataset, the latter plurality of images being referred to hereafter as object images, - attributing a score to each of said object images, based on the distances between said plurality of object images and the one or more query images, wherein the query images, the object images and the definition of the score are chosen in such a manner that the score is representative of the one or more characteristics of the images, at least in a given range of said one or more characteristics, - extracting the process limits from the relation between the score and the one or more process parameters.