bertama,github

absa-pytorch

Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。

aeids-py

AEIDS is a prototype of anomaly-based intrusion detection system which works by remembering the pattern of legitimate network traffic using Autoencoder.

alpr_utils

ALPR model in unconstrained scenarios for Chinese license plates

cs224n_learning_note

Stanford cs224n. 斯坦福2019最新cs224n学习资料个人学习笔记和解读以及作业解答。 http://web.stanford.edu/class/cs224n/

danet

Dual Attention Network for Scene Segmentation (CVPR2019)

deeptraffic

Deep Learning models for network traffic classification

end-to-end-for-chinese-plate-recognition

基于u-net，cv2以及cnn的中文车牌定位，矫正和端到端识别软件，其中unet和cv2用于车牌定位和矫正，cnn进行车牌识别，unet和cnn都是基于tensorflow的keras实现

fake_chs_lp

Generate the fake Chinese license plate images for detection & recognition

fs-net

Code for “FS-Net: A Flow Sequence Network For Encrypted Traffic Classification”

han

Hierachical Attention Networks for Document Classification in Pytorch

hierarchical-attention-networks-pytorch

Hierarchical Attention Networks for document classification

insightface

Face Analysis Project on MXNet and PyTorch

kdd99-cnn-1

Intrusion Detection Based on Convolutional Neural Network with kdd99 data set

long-tailed-recognition.pytorch

[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS). It is also a PyTorch implementation of the NeurIPS 2020 paper 'Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect'.

lz168.github.io

Build a Jekyll blog in minutes, without touching the command line.

mampf

Code for “MaMPF: Encrypted Traffic Classification Based on Multi-Attribute Markov Probability Fingerprints”

multitasktrafficclassification

Multitask Learning Approach for Network Traffic Classification

nltk_data

NLTK Data

pkt2flow

A simple utility to classify packets into flows. It's so simple that only one task is aimed to finish. For Deep Packet Inspection or flow classification, it's so common to analyze the feature of one specific flow. I have make the attempt to use made-ready tools like tcpflows, tcpslice, tcpsplit, but all these tools try to either decrease the trace volume (under requirement) or resemble the packets into flow payloads (over requirement). I have not found a simple tool to classify the packets into flows without further processing. This is why this program is born.

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