Dual-Attentive-Tree-aware-Embedding

Fraud detector

Develops a machine learning model to classify and rank customs fraud cases based on transaction-level data and tree-based features

DATE: Dual Attentive Tree-aware Embedding for Customs Frauds Detection

GitHub

61 stars
10 watching
19 forks
Language: HTML
last commit: over 3 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
yingtongdou/care-gnn An implementation of a graph neural network-based fraud detector designed to counter camouflaged fraudsters 246
zhangtp1996/openfe_reproduce Reproduce experiments and results from a research paper on fraud detection using machine learning algorithms. 3
ai4risk/antifraud Develops and evaluates machine learning models for detecting financial fraud 174
safe-graph/dgfraud A toolbox for building and comparing graph neural network-based fraud detection models 693
0x4d31/deception-as-detection Maps deception detection techniques to the ATT&CK framework and provides documentation for security professionals 285
seondong/customs-fraud-detection A framework for simulating customs fraud detection by integrating machine learning models and data from import declarations. 30
safe-graph/ugfraud A toolbox for unsupervised graph-based fraud detection using multiple algorithms and techniques 129
vxy10/p5_vehicledetection_unet Develops an object detection algorithm using a U-Net architecture to detect vehicles in images and videos from a publicly available dataset 95
iloveai2019/ocan A framework for detecting fraud using a novel neural network approach that learns from benign user data 23
adoreste/truehunter Detects encrypted files using a fast and memory efficient approach without external dependencies. 30
panpanzheng/safe Develops a survival analysis-based model to detect fraud early 34
jingzhang617/cod-rank-localize-and-segment Develops a system to detect, segment, and rank camouflaged objects in images. 74
ditekshen/detection Detects malicious network and host activity using Yara, Snort, and ClamAV signatures. 207
rifkybujana/fnd A machine learning-based system to predict whether news articles are fake or not 8
bharath272/sds_eccv2014 A Matlab implementation of simultaneous object detection and segmentation using deep learning techniques. 96