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C

cqylunlun/GLASS

0
View on GitHub↗
0 stars·0 forks·8 views

GLASS

Features

  • Anomaly Detection - Listed in the “Anomaly detection” section of the Ailia Models awesome list.

Star history

Star history chart for cqylunlun/glassStar history chart for cqylunlun/glass

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What are the main features of cqylunlun/glass?

The main features of cqylunlun/glass are: Anomaly Detection.

Which projects share features with cqylunlun/glass?

Projects with overlapping indexed features include: byungjae89/mahalanobisad-pytorch. byungjae89/spade-pytorch — PyTorch implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences". gitihubi/deepai — An interactive lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of… hcw-00/patchcore_anomaly_detection. xiahaifeng1995/padim-anomaly-detection-localization-master — This is an unofficial implementation of the paper “PaDiM: a Patch Distribution Modeling Framework for Anomaly…

Projects sharing features with GLASS

These projects share indexed features with GLASS. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • byungjae89/mahalanobisad-pytorchB

    byungjae89/MahalanobisAD-pytorch

    0View on GitHub↗
    View on GitHub↗0
  • byungjae89/spade-pytorchbyungjae89 avatar

    byungjae89/SPADE-pytorch

    255View on GitHub↗

    PyTorch implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences"

    Python
    View on GitHub↗255
  • gitihubi/deepaiG

    GitiHubi/deepAI

    0View on GitHub↗

    An interactive lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The the lab content is based on Python, IPython Notebook, and PyTorch.

    View on GitHub↗0
  • hcw-00/patchcore_anomaly_detectionH

    hcw-00/PatchCore_anomaly_detection

    0View on GitHub↗
    View on GitHub↗0
Compare all 5 related projects→