Speaker
Abdulameer Nour
(HUN-REN Wigner Physics Research Center)
Description
RESNET (Residual Networks) is a deep learning architecture that has shown exceptional performance in image classification tasks. In this work, we apply a pre-trained RESNET model to classify and analyze laser crater data, leveraging its ability to capture complex patterns in high-dimensional datasets. The RESNET architecture provides a robust framework for improving the accuracy and speed of classification tasks, making it an ideal choice for the automated analysis of laser-induced craters and similar applications in material science.
Primary author
Abdulameer Nour
(HUN-REN Wigner Physics Research Center)
