DSAwDL

Damage Sites Analysis Damage Sites Analysis with Deep Learning. In this program we tried to get the statistic over damage sites in DP800 steel, where the damage sites are categorized to Inclusions and Non-Inclusions, Which is a measure of ductility. The used network is Inception V3 in which about 10 layers are frozen and the dataset in created in IMM-RWTH using labelImg software by manual definition of the damage sites. This envirement is the corresponding MATLAB-version for 1st classification network behind the presented Web-Interface which is Python-Tensorflow based. The idea behind this Github is to introduce the pipeline in a more conviniet envirement and welcome other researchers to contribute. To use the algorithm please clone the repository to your system and start trying the All_In_One script. The network is already trained and <ou do not need to trained it again. The architecture of the network has been provided for the information of the user. Besides, some further information can be found in the documentations of the script. For your information the MATLAB version of your current system should be above 2018 to be able to run our codes.