[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

anomaly detection with anomalize and Google Trends data

Resources for working with time series and sequence data

Inspired from Mask R-CNN to build a multi-task learning, two-branch architecture: one branch based on YOLOv2 for object detection, the other branch for instance segmentation. Simply tested on Rice and Shapes. MobileNet supported.

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

yolo3 implement by tensorflow， including mobilenet_v1, mobilenet_v2

An R package for space-time anomaly detection using scan statistics.

Digital Cell Sorter (DCS): single cell RNA-seq analysis toolkit. Documentation:

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

fast implementation of singular spectrum transformation (change point detection algorithm)

Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

Computer vision library for wildfire detection

Tensorflow 2 Faster-RCNN implementation from scratch supporting to the batch processing with MobileNetV2 and VGG16 backbones

⭐ An anomaly-based intrusion detection system.

benfordslaw is about the frequency distribution of leading digits.

Deep learning model to estimate the depth of image.

OpenSnitch is a GNU/Linux application firewall