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  2. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.

  3. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Each file represents a single experiment and contains a single anomaly. The dataset represents a multivariate time series collected from the sensors installed on the testbed. There are two markups for Outlier detection (point anomalies) and Changepoint detection (collective anomalies) problems 30+ files (v0.9) CSV Anomaly detection

  4. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    Three broad categories of anomaly detection techniques exist. [1] Supervised anomaly detection techniques require a data set that has been labeled as "normal" and "abnormal" and involves training a classifier. However, this approach is rarely used in anomaly detection due to the general unavailability of labelled data and the inherent ...

  5. Caffe (software) - Wikipedia

    en.wikipedia.org/wiki/Caffe_(software)

    Download QR code; Print/export ... Anomaly detection; Data cleaning; AutoML; ... List of datasets in computer vision and image processing;

  6. Isolation forest - Wikipedia

    en.wikipedia.org/wiki/Isolation_forest

    Anomaly detection with Isolation Forest is done as follows: [4] Use the training dataset to build some number of iTrees; For each data point in the test set: Pass it through all the iTrees, counting the path length for each tree; Assign an “anomaly score” to the instance

  7. Anomaly Detection at Multiple Scales - Wikipedia

    en.wikipedia.org/wiki/Anomaly_Detection_at...

    Download QR code; Print/export ... Anomaly Detection at Multiple Scales; Establishment: 2011: ... Using multiple datasets from Wikipedia, ...

  8. Local outlier factor - Wikipedia

    en.wikipedia.org/wiki/Local_outlier_factor

    In anomaly detection, the local outlier factor (LOF) is an algorithm proposed by Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng and Jörg Sander in 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.

  9. Zeek - Wikipedia

    en.wikipedia.org/wiki/Zeek

    Zeek's event engine analyzes live or recorded network traffic to generate neutral event logs. Zeek uses common ports and dynamic protocol detection (involving signatures as well as behavioral analysis) to identify network protocols. [12] Developers write Zeek policy scripts in the Turing complete Zeek scripting language. By default Zeek logs ...