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18 search results found

Time Series Prediction ⭐ 762

tfts: Time series deep learning models in TensorFlow

Hilo Mpc ⭐ 92

HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems

Rls Neural Net ⭐ 42

Recursive Leasting Squares (RLS) with Neural Network for fast learning

Neural-Kalman GNSS/INS Navigation for Precision Agriculture

Kalmanpy ⭐ 27

Implementation of Kalman Filter in Python

Pose Estimation Ekf ⭐ 24

3D Pose Estimation of the Planar Robot Using Extended Kalman Filter

Dissertation ⭐ 20

Zheng Zhao's doctoral dissertation from Aalto University

Da_tutorial ⭐ 13

This is a 'hands-on' tutorial for the RIKEN International School on Data Assimilation (RISDA2018).

Udacity Self Driving Car ⭐ 11

Self-Driving Engineer Car Nanodegree

A collection of algorithms done in JavaScript with visual demos

Wsn_localization_tracking ⭐ 8

Detection Estimation Learning ⭐ 8

Python notebooks for my graduate class on Detection, Estimation, and Learning. Intended for in-class demonstration. Notebooks illustrate a variety of concepts, from hypothesis testing to estimation to image denoising to Kalman filtering. Feel free to use or modify for your instruction or self-study.

Locatemybus ⭐ 7

IoT and ML to assuage the uncertainty associated with city bus commute. Track live running status and avail tentative schedule of buses. Minimal IoT setup with a central ML-driven web-backend.

Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes

Radar Detecting And Tracking ⭐ 7

ECE 2595 Radar Signal Processing Projects

Self Driven Vehicle using AI in Robotics ,i.e., Kalman filters, A* algorithm, PID control, localization, etc.The basic functionality of this car is just to chase and catch the running away car just like cops. For this, the car is such designed that is takes all the desired steps on its own in order to catch the running away car safely on a high traffic lane.

Qubic_engine ⭐ 5

Collection of C++ based algorithms on numerics, statistics, control, reinforcement learning, machine learning and robotics

Kfestimate.jl ⭐ 5

Julia package for KF and EKF parameter estimation using Automatic Differentiation

Kalman_filter_for_localization_using_python ⭐ 5

Kalman filters are really good at taking noisy sensor data and smoothing out the data to make more accurate predictions. For autonomous vehicles, Kalman filters can be used in object tracking. A Kalman filter does this by weighing the uncertainty in your belief about the location versus the uncertainty in the lidar or radar measurement. If your belief is very uncertain, the Kalman filter gives more weight to the sensor. If the sensor measurement has more uncertainty, your belief about the locati

Neurosymbolic Tinyml ⭐ 5

TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning

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