2023年8月3日 · Built using NASA's Harmonized Landsat and Sentinel-2 dataset, the release of the HLS Geospatial Foundation Model (HLS Geospatial FM) is a milestone in the application of AI for Earth science. The model has a wide range of potential applications, including tracking changes in land use, monitoring natural disasters, and predicting crop yields.

This repository contains examples of fine-tuning Harmonized Landsat and Sentinel-2 (HLS) Prithvi foundation model. Topics

2023年8月3日 · To tailor the model for Earth observation analysis, NASA’s Harmonized Landsat and Sentinel-2 imagery was used as the training data for the HLS Geospatial Foundation Model (HLS Geospatial FM). The model was released to the public on Thursday, August 3 via Hugging Face, a data science platform that enables machine learning developers to openly ...

High-level synthesis (HLS), sometimes referred to as C synthesis, electronic system-level (ESL) synthesis, algorithmic synthesis, or behavioral synthesis, is an automated design process that takes an abstract behavioral specification of a digital system and finds a register-transfer level structure that realizes the given behavior.

2023年12月7日 · Foundation models are often trained on text-based documents, but IBM’s new geospatial foundation model was uniquely built using Earth surface reflectance data from NASA’s Harmonized Landsat Sentinel-2 (HLS) data products. HLS data is used routinely for environmental monitoring and data production is managed, in part, by the IMPACT HLS team.

This page documents our hls_model class usage. You can generate generate an hls model object from a keras model through hls4ml's API:

2025年3月17日 · We create firmware implementations of machine learning algorithms using high level synthesis language (HLS). We translate traditional open-source machine learning package models into HLS that can be configured for your use-case!

hls4ml.utils.plot. plot_model (model, to_file = 'model.png', show_shapes = False, show_layer_names = True, show_precision = False, rankdir = 'TB', dpi = 96) Converts a HLS model to dot format and save to a file. Parameters: model – A HLS model instance. to_file – File name of the plot image. show_shapes – whether to display shape information.

hls4ml是一个专为FPGA上实现机器学习推理而设计的开源软件包。它利用高级综合语言（HLS）将传统开源机器学习模型转化为可配置的固件，从而实现高效推理。项目提供详尽的文档和教程，适用于快速入门和深入研究。用户可以通过GitHub平台参与讨论和贡献。

A package for machine learning inference in FPGAs. We create firmware implementations of machine learning algorithms using high level synthesis language (HLS). We translate traditional open-source machine learning package models into …