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

Last update: Jan 30, 2022

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Deep Learning SSIDprobeCollector

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:

Collect SSID Probes against a timeline and location
Collect video or photo against a timeline and location
Diff the probe requests typical for the location with those at the moment of capture
Log multiple times where ML is certain the subject is the same (and unique) storing the result
Where Unique probe requests are identified perform an API lookup on https://www.wigle.net and store SSID,Photo & and map result
If Wigle lookup fails just store the correlated data.

Owner

Bill Reyor

Security Architecture & Incident Response.

GitHub Repository

Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method

C++/ROS Source Codes for "Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method" published in IEEE Trans. Intelligent Transportation Systems

88 Dec 23, 2022

Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)

Inter-Prototype (BMVC 2021): Official Project Webpage This repository provides the official PyTorch implementation of the following paper: Improving F

16 Jun 30, 2022

An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.

简介通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型，分别是SimpleCNN和MiniXception。利用 imdb_crop

8 Mar 11, 2022

Code for the Higgs Boson Machine Learning Challenge organised by CERN & EPFL

A method to solve the Higgs boson challenge using Least Squares - Novae This project is the Project 1 of EPFL CS-433 Machine Learning. The project is

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This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".

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105 Dec 06, 2022

This is an official implementation for "AS-MLP: An Axial Shifted MLP Architecture for Vision".

AS-MLP architecture for Image Classification Model Zoo Image Classification on ImageNet-1K Network Resolution Top-1 (%) Params FLOPs Throughput (image

106 Dec 12, 2022

A framework to train language models to learn invariant representations.

Invariant Language Modeling Implementation of the training for invariant language models. Motivation Modern pretrained language models are critical co

6 Nov 16, 2022

An SMPC companion library for Syft

SyMPC A library that extends PySyft with SMPC support SyMPC /ˈsɪmpəθi/ is a library which extends PySyft ≥0.3 with SMPC support. It allows computing o

0 Oct 13, 2021

PyTorch implementation for OCT-GAN Neural ODE-based Conditional Tabular GANs (WWW 2021)

OCT-GAN: Neural ODE-based Conditional Tabular GANs (OCT-GAN) Code for reproducing the experiments in the paper: Jayoung Kim*, Jinsung Jeon*, Jaehoon L

7 Dec 27, 2022

DFM: A Performance Baseline for Deep Feature Matching

DFM: A Performance Baseline for Deep Feature Matching Python (Pytorch) and Matlab (MatConvNet) implementations of our paper DFM: A Performance Baselin

143 Jan 02, 2023

Immortal tracker

Immortal_tracker Prerequisite Our code is tested for Python 3.6. To install required liabraries: pip install -r requirements.txt Waymo Open Dataset P

74 Dec 03, 2022

CarND-LaneLines-P1 - Lane Finding Project for Self-Driving Car ND

Finding Lane Lines on the Road Overview When we drive, we use our eyes to decide where to go. The lines on the road that show us where the lanes are a

769 Dec 27, 2022

Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges for the practitioner

Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges

1 Apr 30, 2021

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

Related tags

Overview

SSIDprobeCollector

Owner

Bill Reyor

Autonomous Driving on Curvy Roads without Reliance on Frenet Frame: A Cartesian-based Trajectory Planning Method

Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)

An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.

Code for the Higgs Boson Machine Learning Challenge organised by CERN & EPFL

This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".

This is an official implementation for "AS-MLP: An Axial Shifted MLP Architecture for Vision".

A framework to train language models to learn invariant representations.

An SMPC companion library for Syft

PyTorch implementation for OCT-GAN Neural ODE-based Conditional Tabular GANs (WWW 2021)

DFM: A Performance Baseline for Deep Feature Matching

Immortal tracker

CarND-LaneLines-P1 - Lane Finding Project for Self-Driving Car ND

Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges for the practitioner

【CVPR 2021, Variational Inference Framework, PyTorch】 From Rain Generation to Rain Removal

Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features

How to use TensorLayer

Jittor implementation of Recursive-NeRF: An Efficient and Dynamically Growing NeRF

Black-Box-Tuning - Black-Box Tuning for Language-Model-as-a-Service

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion

Computationally efficient algorithm that identifies boundary points of a point cloud.