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Welcome to the anomaly-detection wiki page!

Initial Goal for the page:

1. Literature review with prime focus on:

• Paper name and its significance
• Types of models being used.
• Benchmark on performance or any other parameter.

2. Personal Contribution:

• Data handling and preprocessing
• Model Implementation
• Model Evaluation

3. Anything apart from the mentioned above worth a note.

U- net Implementation on MRI data

Initial Thoughts on the dataset..

Research Paper Insights

1. Classification Based Anomaly Detection for General Data

2. Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

3. Attention Guided Anomaly Localization in Images

4. BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

5. Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings

6. Discriminative Reconstruction Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection