27 citations · 47 across the 4 of their papers we have counts for
4 papers
Utilizing Generative Adversarial Networks for Image Data Augmentation and Classification of Semiconductor Wafer Dicing Induced Defects
Zhining Hu, Tobias Schlosser, Michael Friedrich +3
In semiconductor manufacturing, the wafer dicing process is central yet vulnerable to defects that significantly impair yield - the proportion of defect-free chips. Deep neural net…
Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning
Frederik Beuth, Tobias Schlosser, Michael Friedrich +1
It is a long-term goal to transfer biological processing principles as well as the power of human recognition into machine vision and engineering systems. One of such principles is…
Hexagonal Image Processing in the Context of Machine Learning: Conception of a Biologically Inspired Hexagonal Deep Learning Framework
Tobias Schlosser, Michael Friedrich, Danny Kowerko
Inspired by the human visual perception system, hexagonal image processing in the context of machine learning deals with the development of image processing systems that combine th…
A Novel Visual Fault Detection and Classification System for Semiconductor Manufacturing Using Stacked Hybrid Convolutional Neural Networks
Tobias Schlosser, Frederik Beuth, Michael Friedrich +1
Automated visual inspection in the semiconductor industry aims to detect and classify manufacturing defects utilizing modern image processing techniques. While an earliest possible…