An ML & Correlation platform for transforming disparate data points of interest into usable intelligence.

Overview

SSIDprobeCollector

An ML & Correlation platform for transforming disparate data points of interest into usable intelligence.

At a High level the platform will do the following in its most basic operational state:

  1. Collect SSID Probes against a timeline and location
  2. Collect video or photo against a timeline and location
  3. Diff the probe requests typical for the location with those at the moment of capture
  4. Log multiple times where ML is certain the subject is the same (and unique) storing the result
  5. Where Unique probe requests are identified perform an API lookup on https://www.wigle.net and store SSID,Photo & and map result
  6. If Wigle lookup fails just store the correlated data.
Owner
Bill Reyor
Security Architecture & Incident Response.
Bill Reyor
Spiking Neural Network for Computer Vision using SpikingJelly framework and Pytorch-Lightning

Spiking Neural Network for Computer Vision using SpikingJelly framework and Pytorch-Lightning

Sami BARCHID 2 Oct 20, 2022
Gesture recognition on Event Data

Event based Gesture Recognition Gesture recognition on Event Data usually involv

2 Feb 14, 2022
Semi-Supervised Learning for Fine-Grained Classification

Semi-Supervised Learning for Fine-Grained Classification This repo contains the code of: A Realistic Evaluation of Semi-Supervised Learning for Fine-G

25 Nov 08, 2022
Machine Translation Implement By Bi-GRU And Transformer

Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be

He Wang 2 Oct 27, 2021
September-Assistant - Open-source Windows Voice Assistant

September - Windows Assistant September is an open-source Windows personal assis

The Nithin Balaji 9 Nov 22, 2022
noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.

ProSelfLC: CVPR 2021 ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks For any specific discussion or potential fu

amos_xwang 57 Dec 04, 2022
ALFRED - A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

ALFRED A Benchmark for Interpreting Grounded Instructions for Everyday Tasks Mohit Shridhar, Jesse Thomason, Daniel Gordon, Yonatan Bisk, Winson Han,

ALFRED 204 Dec 15, 2022
Author: Wenhao Yu ([email protected]). ACL 2022. Commonsense Reasoning on Knowledge Graph for Text Generation

Diversifying Commonsense Reasoning Generation on Knowledge Graph Introduction -- This is the pytorch implementation of our ACL 2022 paper "Diversifyin

DM2 Lab @ ND 61 Dec 30, 2022
Deep generative models of 3D grids for structure-based drug discovery

What is liGAN? liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grid

Matt Ragoza 152 Jan 03, 2023
This repository holds code and data for our PETS'22 article 'From "Onion Not Found" to Guard Discovery'.

From "Onion Not Found" to Guard Discovery (PETS'22) This repository holds the code and data for our PETS'22 paper titled 'From "Onion Not Found" to Gu

Lennart Oldenburg 3 May 04, 2022
Employs neural networks to classify images into four categories: ship, automobile, dog or frog

Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic

Riley Baker 1 Jan 18, 2022
Repo for 2021 SDD assessment task 2, by Felix, Anna, and James.

SoftwareTask2 Repo for 2021 SDD assessment task 2, by Felix, Anna, and James. File/folder structure: helloworld.py - demonstrates various map backgrou

3 Dec 13, 2022
Pytorch implementation of "Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet"

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

蒋子航 383 Dec 27, 2022
Repository for the NeurIPS 2021 paper: "Exploiting Domain-Specific Features to Enhance Domain Generalization".

meta-Domain Specific-Domain Invariant (mDSDI) Source code implementation for the paper: Manh-Ha Bui, Toan Tran, Anh Tuan Tran, Dinh Phung. "Exploiting

VinAI Research 12 Nov 25, 2022
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation

DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning

HiEST 2 Sep 09, 2022
Ganilla - Official Pytorch implementation of GANILLA

GANILLA We provide PyTorch implementation for: GANILLA: Generative Adversarial Networks for Image to Illustration Translation. Paper Arxiv Updates (Fe

Samet Hi 462 Dec 05, 2022
Contrastive Learning Inverts the Data Generating Process

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

71 Nov 25, 2022
Official Implementation of SWAGAN: A Style-based Wavelet-driven Generative Model

Official Implementation of SWAGAN: A Style-based Wavelet-driven Generative Model SWAGAN: A Style-based Wavelet-driven Generative Model Rinon Gal, Dana

55 Dec 06, 2022
Official pytorch implementation of Rainbow Memory (CVPR 2021)

Rainbow Memory: Continual Learning with a Memory of Diverse Samples

Clova AI Research 91 Dec 17, 2022
PyTorch reimplementation of the paper Involution: Inverting the Inherence of Convolution for Visual Recognition [CVPR 2021].

Involution: Inverting the Inherence of Convolution for Visual Recognition Unofficial PyTorch reimplementation of the paper Involution: Inverting the I

Christoph Reich 100 Dec 01, 2022