From 00149eff4e85fefae1993f76a632c8eece370699 Mon Sep 17 00:00:00 2001 From: Wei ZHANG Date: Thu, 1 Feb 2024 12:33:28 +0800 Subject: [PATCH] =?UTF-8?q?=E2=9C=A8=20Add=20AeBAD=20Aircraft=20Engine=20B?= =?UTF-8?q?lade=20Anomaly=20Detection,=20BeanTech=20Anomaly=20Detection(BT?= =?UTF-8?q?AD)v?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) diff --git a/README.md b/README.md index f4c9d704..e1a83373 100644 --- a/README.md +++ b/README.md @@ -64,6 +64,8 @@ Important critical papers from year 2017 have been collected and compiled, which - [MVTEC ITODD](#16MVTEC-ITODD) - [BSData](#17bsdata---dataset-for-instance-segmentation-and-industrial-wear-forecasting) - [GID: The Gear Inspection Dataset](#18the-gear-inspection-dataset) + - [AeBAD aircraft engine blade anomaly detection](#19AeBAD-aircraft-engine-blade-anomaly-detection) + - [BeanTech Anomaly Detection(BTAD)](#20BeanTech-Anomaly-Detection(BTAD)) - [More Inventory](#3-more-inventory-of-the-best-data-set-sources) - [Papers](#4-surface-defect-detection-papers) - [Acknowledgements](#acknowledgements) @@ -449,6 +451,27 @@ The Gear Inspection Dataset (GID) is a dataset for a competition held by Baidu ( 👆 [BACK to Table of Contents -->](#table-of-contents) + +### 19）AeBAD Aircraft Engine Blade Anomaly Detection + +Download link: http://suo.nz/2IU48P + +The real-world aero-engine blade anomaly detection (AeBAD) data set consists of two sub-data sets: the single blade data set (AeBAD-S) and the blade video anomaly detection data set (AeBAD-V). Compared with existing datasets, AeBAD has the following two characteristics: 1.) The target samples are not aligned and at different scales. 2.) There is a domain shift in the distribution of normal samples in the test set and training set, where the domain shift is mainly caused by changes in illumination and view. + +![image](https://github.com/Charmve/Surface-Defect-Detection/assets/29084184/746e2264-c232-426f-8b7e-897a02b31800) + +👆 [BACK to Table of Contents -->](#table-of-contents) + +### 20）BeanTech Anomaly Detection(BTAD) + +Download Link：http://suo.nz/2JEGEi + +The BTAD (BeanTech Anomaly Detection) dataset is a real-world industrial anomaly dataset. This dataset contains a total of 2830 real-world images of 3 industrial products. + +![image](https://github.com/Charmve/Surface-Defect-Detection/assets/29084184/3167de0b-bdf9-4b0a-b99e-fb4791fd1510) + +👆 [BACK to Table of Contents -->](#table-of-contents) +
## 3. More Inventory of the Best Data Set Sources