Supplementary Materials of Paper: To What Extent Do DNN-based Image Classification Models Make Unreliable Inferences?
This page hosts the Supplementary Materials of Paper: To What Extent Do DNN-based Image Classification Models Make Unreliable Inferences?
The paper is accepted by the Journal Empirical Software Engineering in May 2021
Feel free to contact the author if you have any questions.
Please see the folder source_code.
The implementation of our approach is not hard. We upload our implementation for your reference. Let us know if you have any questions.
The basic data is in the folder csv_file.
These files are generated by the analyze_result.py.
The raw experiment data is in npz format. It is relative large (>100MB) and we are looking for some places to store it. Let us know if anything you want but has not appear in this website. We will try to figure out a way to share a copy with you somehow.
Besides, we have all the checkpoints (~100 epochs for each model) in the training of the PyTroch ResNet50 and VGG16. They are in huge size (>10 GB) and we cannot share it here. Training it is very time-consuming. Let us know if you want to have a copy for your research.
The supplementary data of our first submission now moves to in the folder csv_file_archive.
It is only for archive.
Please do not use it any more.