awesome-TS-anomaly-detection VS Awesome-Geospatial

Compare awesome-TS-anomaly-detection vs Awesome-Geospatial and see what are their differences.

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awesome-TS-anomaly-detection Awesome-Geospatial
72 12
2,811 3,846
- -
0.0 7.1
2 months ago 8 days ago
- Creative Commons Zero v1.0 Universal
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-TS-anomaly-detection

Posts with mentions or reviews of awesome-TS-anomaly-detection. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2020-12-31.

Awesome-Geospatial

Posts with mentions or reviews of Awesome-Geospatial. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-11.

What are some alternatives?

When comparing awesome-TS-anomaly-detection and Awesome-Geospatial you can also consider the following projects:

openHistorian - The Open Source Time-Series Data Historian

awesome-gis - ๐Ÿ˜ŽAwesome GIS is a collection of geospatial related sources, including cartographic tools, geoanalysis tools, developer tools, data, conference & communities, news, massive open online course, some amazing map sites, and more.

awesome-metric-learning - ๐Ÿ˜Ž A curated list of awesome practical Metric Learning and its applications

the-book-of-secret-knowledge - A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.

Netdata - The open-source observability platform everyone needs

awesome-list - Cybersecurity oriented awesome list

NAB - The Numenta Anomaly Benchmark

awesome - ๐ŸŒŸ My Awesome Repositories List. Automatically updates by GitHub Actions on UTC 00:00 & 16:00

A3 - Inspired by recent advances in coverage-guided analysis of neural networks, we propose a novel anomaly detection method. We show that the hidden activation values contain information useful to distinguish between normal and anomalous samples. Our approach combines three neural networks in a purely data-driven end-to-end model. Based on the activation values in the target network, the alarm network decides if the given sample is normal. Thanks to the anomaly network, our method even works in strict semi-supervised settings. Strong anomaly detection results are achieved on common data sets surpassing current baseline methods. Our semi-supervised anomaly detection method allows to inspect large amounts of data for anomalies across various applications.

Super_Cool_Links_By_Sera - A collection of awesome links I've compiled that are related to cybersecurity.

pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

awesome-bookmarks - :sparkling_heart: A curated list of awesome things