The scope of this master thesis is to build an (semi)automatic system to train a Siamese net to find the similarity of the fasteners (namely bolts, nuts, screws and washers). Using the output of the Siamese net, the system should group and sort the fasteners in similar groups (in a fine-grained manner. For example it should put all the AS1800 bolts in one group and all the MS2650 bolts in another one). To successfully undertake this thesis, you need to have solid knowledge on machine learning and convolutional neural networks, together with experience in Python programming and working with at least one deep learning framework (Keras, PyTorch, TensorFlow).