Research Thesis Student - Institute For Signal Processing And Systems Theory
Stuttgart, Baden-Württemberg, Germany
Grade: 1.3(Sehr Gut)/1.0(Best Grade)Topic: Improving Domain Generalization of Image to Image translation models using Deep Neural Network-Main application of the project was to develop techniques such that autonomousvehicles can be able to segment road scenes reasonably well on foggy, noisy real worldimage data which it had not seen during training.-Trained the developed model on Cityscapes(free from real-world fog, noise), validated on a different domain -GTA, evaluated on foggy cityscapes datasets.-Researched ways to make the model independent of the input data's style and texture by implementing various techniques.-Developed a user-selectable channel-wise Batch/Instance Normalization block whichimproved the overall generalization on the unseen domain from mIoU 45% to 46.94%-Finally improved the generalizability of a standard state-of-the-art image segmentationmodel RobustNetDepartment: Institut für Signalverarbeitung und Systemtheorie (ISS)Supervisor : Chenming JiangExaminer: Prof Dr Ing. Bin Yang*Tags: DeepLabV3+, IBN-Net, PSPNet, Semantic Segmentation, Pytorch, Computer Vision