eliastor's starred repositories
You-Dont-Know-JS
A book series on JavaScript. @YDKJS on twitter.
javascript
JavaScript Style Guide
excalidraw
Virtual whiteboard for sketching hand-drawn like diagrams
33-js-concepts
📜 33 JavaScript concepts every developer should know.
javascript-questions
A long list of (advanced) JavaScript questions, and their explanations :sparkles:
LLaMA-Factory
Unify Efficient Fine-Tuning of 100+ LLMs
awesome-godot
A curated list of free/libre plugins, scripts and add-ons for Godot
reddit-top-2.5-million
This is a dataset of the all-time top 1,000 posts, from the top 2,500 subreddits by subscribers, pulled from reddit between August 15–20, 2013.
Indoor-Positioning-And-Navigation-Algorithms
Strongly accurate indoor positioning algorithms with the main focus on indoor navigation developed by Navigine company. Here we will step by step publish the source code of our algorithm starting with trilateration.
In-outdoorSeamlessPositioningNavigationSystem
[Esri GIS 2nd Prize] We developed this indoor and outdoor seamless positioning and navigation system under the Android system by using the built-in multi-sensors of mobile phones.
llama-cpp-wasm
WebAssembly (Wasm) Build and Bindings for llama.cpp
TopologicalSemanticGraphMemory
Topological Semantic Graph Memory for Image Goal Navigation (CoRL 2022 oral)
AugmentedRealityIndoorNavigation
AR app for indoor navigation using ARcore and Sceneform.
PointNav-VO
[ICCV 2021] Official implementation of "The Surprising Effectiveness of Visual Odometry Techniques for Embodied PointGoal Navigation"
SLAM-on-Raspberry-Pi
Robotic Localization with SLAM on Raspberry Pi integrated with RP LIDAR A1. Point Cloud remote visualization doing using MQTT in real-time.
Indoor-Positioning-System
An indoor positioning system (IPS) is a system to locate objects or people inside a building using radio waves, magnetic fields, acoustic signals, or other sensory information.
Recurrent_Neural_Networks_for_Accurate_RSSI_Indoor_Localization
Source code for M.T. Hoang, B. Yuen, X. Dong, T. Lu, R. Westendorp and K. Reddy, “Recurrent Neural Networks for Accurate RSSI Indoor Localization,” IEEE Internet of Things Journal, 2019