iiiwan

iiiwan's Stars

• ShiArthur03/ShiArthur03

  Language:MATLAB10.4k321.4k1.9k

• run-llama/rags

  Build ChatGPT over your data, all with natural language

  Language:Python6.2k5539638

• ML4Comm-Netw/Paper-with-Code-of-Wireless-communication-Based-on-DL

  无线与深度学习结合的论文代码整理/Paper-with-Code-of-Wireless-communication-Based-on-DL

  1.8k33922639

• iCGY96/awesome_OpenSetRecognition_list

  A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition

  1.1k379145

• jxgu1016/MNIST_center_loss_pytorch

  A PyTorch implementation of center loss on MNIST

  Language:Python362102189

• hendrycks/ss-ood

  Self-Supervised Learning for OOD Detection (NeurIPS 2019)

  Language:Python26482531

• Michedev/VAE_anomaly_detection

  Language:Python18981139

• A03ki/f-AnoGAN

  Implementation of f-AnoGAN with PyTorch

  Language:Python12831235

• hiram64/ocsvm-anomaly-detection

  anomaly detection by one-class SVM

  Language:Python833717

• meysamsadeghi/Security-and-Robustness-of-Deep-Learning-in-Wireless-Communication-Systems

  A research oriented repository on the Security and Robustness of Deep Learning for Wireless Communication Systems

  Language:Jupyter Notebook837252

• aadeshnpn/OSDN

  Keras implementation for the research paper "Towards Open Set Deep Networks" A Bendale, T Boult, CVPR 2016

  Language:Jupyter Notebook7731721

• nazim1021/OOD-detection-using-OECC

  Outlier Exposure with Confidence Control for Out-of-Distribution Detection

  Language:Jupyter Notebook69518

• harshilpatel1799/Iot-Cyber-Security-with-Machine-Learning-Research-Project

  IoT networks have become an increasingly valuable target of malicious attacks due to the increased amount of valuable user data they contain. In response, network intrusion detection systems have been developed to detect suspicious network activity. UNSW-NB15 is an IoT-based network traffic data set with different categories for normal activities and malicious attack behaviors. UNSW-NB15 botnet datasets with IoT sensors' data are used to obtain results that show that the proposed features have the potential characteristics of identifying and classifying normal and malicious activity. Role of ML algorithms is for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets is possible. The ML model metrics using the UNSW-NB15 dataset revealed that ML techniques with flow identifiers can effectively and efficiently detect botnets’ attacks and their tracks.

  Language:Jupyter Notebook5516

• gxhen/LoRa_RFFI

  Language:Python533817

• abdulkarimgizzini/Enhancing_Least_Square_Channel_Estimation_Using_Deep_Learning

  This repository includes the source code of the LS-DNN based channel estimators proposed in "Enhancing Least Square Channel Estimation Using Deep Learning" paper that is published in the proceedings of the 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) virtual conference.

  Language:MATLAB45127

• usnistgov/OFDM-GAN

  Language:Python30204

• qiang5love1314/CSI-dataset

  Real-world datasets for indoor localization

  23153

• YihongDong/SR2CNN-Zero-Shot-Learning-for-Signal-Recognition

  Language:Python21215

• mdelrosa/quadriga-brat

  BRAT Lab files for generating CSI datasets with QuaDRiGa channel model

  Language:MATLAB177

• lucy3589/mlosr

  Language:Python1511

• emanueleg/lora-rssi

  Experimental dataset of LoRa RSSI measurements collected indoor & outdoor

  Language:MATLAB13206

• nghia9691/OSDN

  Try Openmax with MNIST Fashion dataset

  Language:Python11204

• cuteboyqq/GANomaly-Pytorch

  GAN, semi-supervised, abnormal detection

  Language:Python5100

• girmaymerkebu/Technology-Recognition-for-4G-LTE-and-5G-NR

  Implementation of technology recognition model to identify 4G LTE, 5G NR, and Overlap signals. The model is used in our paper titled "Enabling Uncoordinated Dynamic Spectrum Sharing Between LTE and NR Networks".

  Language:Python5100

• fpeci/csi_datasets

  4101

• pedroidc/Pilot-Contamination-Detection-Massive-MIMO

  Repository for pilot contamination detection in Multi User Massive MIMO Systems at the Laboratory of Signal and Systems of the Federal Unievrsity of UFABC.

  Language:Jupyter Notebook44

• ryan-n-may/LSTM_Temporal_Prediction_of_Rayleigh_Channels

  LSTM_Time_Series_Prediction_Rayleigh_Channels

  Language:MATLAB4201

• jgalfaro/mirrored-mimoGAN

  mirrored repositores (public releases from bitbucket/gitlab repositories)

  Language:Python2302

• ewerae/MEng-Detection-of-Adversarial-Attacks-on-Machine-Learning-Based-Wireless-Communication-Systems

  MEng - Research Paper

  Language:Python1

• zanderman/gan-wireless-5g

  ECE 5674 final project "Generative Adversarial Learning for Intelligent 5G Interference Mitigation"

  Language:Jupyter Notebook1101