Real Time Abnormal Event Detection In Crowded Scenes
This project is based on STACOG descriptor to detect anomalous event in real-time
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pysad | 200 |  | 1 | 7 months ago | 3 | October 06, 2023 | 1 | bsd-3-clause | Python | |
| Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data) | ||||||||||
| Mstream | 98 | 4 months ago | apache-2.0 | C++ | ||||||
| Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies. | ||||||||||
| Memstream | 77 | 4 months ago | apache-2.0 | Python | ||||||
| MemStream: Memory-Based Streaming Anomaly Detection | ||||||||||
| Faster Grad Cam | 16 | 4 years ago | mit | Jupyter Notebook | ||||||
| Faster and more precisely than Grad-CAM | ||||||||||
| Real Time Abnormal Event Detection In Crowded Scenes | 9 | 6 years ago | Matlab | |||||||
| This project is based on STACOG descriptor to detect anomalous event in real-time | ||||||||||
| Real Time Ids | 8 | 5 months ago | Python | |||||||
| Real-time Intrusion Detection System implementing Machine Learning. We combine Supervised Learning (Random forest) for detecting known attacks from CICIDS 2018 & SCVIC-APT datasets, and Unsupervised Learning (Auto encoders) for anomaly detection. | ||||||||||
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