Who Cited It

Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

2017 · Lecture notes in computer science · 2,413 citations · 6 from inside this corpus

Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Ursula Schmidt‐Erfurth, Georg Langs

No abstract in the source record.

Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Disco… (2017)Unsupervised Anomaly Detectio…Adam: A Method for Stochastic Optimization (2014)Adam: A Method for Stochastic…A review of novelty detection (2014)A review of novelty detectionMVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection (2019)MVTec AD — A Comprehensive Re…Generative adversarial network in medical imaging: A review (2019)Generative adversarial networ…Causability and explainability of artificial intelligence in medicine (2019)Causability and explainabilit…Deep Learning for Anomaly Detection: A Review (2020)Deep Learning for Anomaly Det…A State-of-the-Art Survey on Deep Learning Theory and Architectures (2019)A State-of-the-Art Survey on …[No title in the source record — Newcastle University ePrints (Newcastle Univesity)][No title in the source recor…
8 of 8 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

PaperYearCited
Adam: A Method for Stochastic Optimization201484,698
A review of novelty detection20141,647

What cites it, inside the corpus

PaperYearCited
MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection20191,999
Generative adversarial network in medical imaging: A review20191,902
Causability and explainability of artificial intelligence in medicine20191,851
Deep Learning for Anomaly Detection: A Review20201,731
A State-of-the-Art Survey on Deep Learning Theory and Architectures20191,619
[No title in the source record — Newcastle University ePrints (Newcastle Univesity)]1,494

Links

DOI · OpenAlex record

Topics

Anomaly Detection Techniques and ApplicationsComputer Science
Retinal Imaging and AnalysisMedicine
Cell Image Analysis TechniquesBiochemistry, Genetics and Molecular Biology

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports5 author record(s) attached.
  • supports20 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:49+00:00.

sha256 a2172c1bbe00c44b…