efficientADAnomalyDetector
Description
The efficientADAnomalyDetector
object detects images of anomalies
using an EfficientAD anomaly detector network. Train the detector using the trainEfficientADAnomalyDetector
function. To detect anomalous images, pass the
trained detector to the classify
function.
Note
This functionality requires Deep Learning Toolbox™ and the Automated Visual Inspection Library for Computer Vision Toolbox™. You can install the Automated Visual Inspection Library for Computer Vision Toolbox from Add-On Explorer. For more information about installing add-ons, see Get and Manage Add-Ons.
Creation
Description
detector = efficientADAnomalyDetector
creates an EfficientAD
anomaly detector from a base patch description network (PDN).
detector = efficientADAnomalyDetector(
specifies options for the EfficientAD anomaly detector creation using one or more
name-value arguments.Name=Value
)
Name-Value Arguments
Properties
Object Functions
predict | Predict unnormalized anomaly scores |
classify | Classify image as normal or anomalous |
anomalyMap | Predict per-pixel anomaly score map |
Examples
More About
References
[1] Batzner, Kilian, Lars Heckler, and Rebecca König. “EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies.” arXiv, February 8, 2024. https://doi.org/10.48550/arXiv.2303.14535.
[2] Sugawara, Shota, and Ryuji Imamura. “PUAD: Frustratingly Simple Method for Robust Anomaly Detection.” In 2024 IEEE International Conference on Image Processing (ICIP), 842–48. Abu Dhabi, United Arab Emirates: IEEE, 2024. https://doi.org/10.1109/ICIP51287.2024.10647438.