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annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

cnn-lstm-bilstm-deepcnn-clstm-in-pytorch

In PyTorch Learing Neural Networks Likes CNN、BiLSTM

cooperative-localization-of-three-vehicles

Estimation of the states and their associated covariance of three vehicles moving around a round-about, the dataset is real and comes from the GNSS and the sensors implanted on the vehicles.

courses-zh-v2

中文版 v2 课程

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

decawave_localization

Localization node for the Decawave Ultra-wide band radios

dgorl

DGORL: Distributed Graph Optimization based Relative Localization of Multi-Robot Systems

dwm1000_indoor_position

UWBandIMU

geardrones

GEARdrones is a lightweight drone control and multiagent localizaion system that combines flight controller, UWB relative localization algorithm, and software monitor.

icra2018_uwb_sensor_fusion

identification-of-nlos-and-mp-in-uwb-using-ml

This experimental research data and src were used to present the multi-label classification results of UWB ranging system in the following open access article. https://doi.org/10.3390/app10113980; Appl. Sci. 2020, 10(11), 3980, MDPI.

identification-of-nlos-causing-material-in-uwb-localization-using-machine-learning-methods

indoor_localization_decawave

This code uses Decawave's UWB technology with a sense hat IMU to estimate the location of a tag node

ins_uwb_positioning

Robust INS/UWB integrated positioning for autonomous indoor mobile robots

learning

My first repository for learning

localization-algorithm

Sensor fusion (UWB+IMU+Ultrasonic), using Kalman filter and 3 different multilateration algorithms (Least square and Recursive Least square and gradient descent)

los-nlos-classification

depend CIR(channel impulse response) to identification LOS or NLOS channel

los-nlos-classification-cnn

UWB LOS-NLOS Signal Classification using CNN

los_nlos_identification

lstm

基于LSTM的时间序列预测研究

lstm-matlab

LSTM-MATLAB is Long Short-term Memory (LSTM) in MATLAB, which is meant to be succinct, illustrative and for research purpose only. It is accompanied with a paper for reference: Revisit Long Short-Term Memory: An Optimization Perspective, NIPS deep learning workshop, 2014.

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

lstm_on_uwb

manifold-learning

Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)

mds-sammonmapping-isomap

The code for Multidimensional Scaling (MDS), Sammon Mapping, and Isomap.

mrs-uwb-sim

Gazebo simulations for modelling and testing relative UWB-based localization in heterogeneous multi-robot systems.

multi-robot-localization

Simulation of a swarm of robots with range-based relative localization

murp-datasets

UWBdataset

positioning-algorithms-for-uwb-matlab

The Matlab scripts for five positioning algorithms regarding UWB localization. The five algorithms are Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Taylor Series-based location estimation, Trilateration, and Multilateration methods.