There are 2 repositories under las topic.
Loaders for big data visualization. Website:
Tools for analyzing aerial point clouds of forest data.
ParaView plugins
Convert various AEC model formats for efficient viewing in the browser with xeokit.
This repo detect objects automatically for LiDAR data
Listen, Attend and spell model for E2E ASR. Implementation in Pytorch
copc-lib provides an easy-to-use reader and writer interface for creating and reading Cloud Optimized Point Clouds, with bindings for Python and C++
PyTorch implementation of automatic speech recognition models.
LAS/LAZ library for C#
LAS Explorer is a Streamlit web app that allows you to understand the contents of a LAS file. Also includes the ability to identify missing data intervals.
JavaScript for converting well-log standard .las file format to json format
An R package for reading Log Ascii Standard (LAS) files for well log data.
Plugin to generate a three light exposure hillshade (shaded relief by combining three light exposures)
:fire: ASR教程: https://dataxujing.github.io/ASR-paper/
Python library for checking conformity of Log ASCII Standard (LAS) files to standards
Open source, public notebooks for working with DLISIO
A Unity demo of the Point Data Abstraction Library (PDAL)
End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.
PyTorch implementation of Listen, Attend and Spell (LAS) speech recognition paper