News

Latest Updates and Announcements from Kraina Lab

SRAI: Towards Standardization of Geospatial AI

Paper presented at the GeoAI @ SIGSPATIAL 2023!

We’re delighted to announce that our submission to the GeoAI workshop at SIGSPATIAL 2023 has been accepted! We’ll be presenting a paper describing our open-source library for geospatial data processing and represenation learning.

Map Diffusion – Text Promptable Map Generation Diffusion Model

Paper presented at the UrbanAI @ SIGSPATIAL 2023!

We’re delighted to announce that our submission to the UrbanAI workshop at SIGSPATIAL 2023 has been accepted! We’ll be presenting a paper describing our open-source library for geospatial data processing and represenation learning.

Utilising OSM data in geospatial representation learning

Lightning talk presented at the OSMScience @ State of the Map 2023!

We’re delighted to announce that our abstract has been accepted! We’ll be an offline lightning talk at the conference. You can find more information in our publications page.

Geospatial Machine Learning Tutorial at ML in PL 2023

Introduction to Geospatial Machine Learning

Members of Kraina AI will be presenting a comprehensive tutorial on geospatial machine learning at the ML in PL Conference 2023 in Warsaw, Poland.

SRAI Tutorial Accepted at EuroSciPy 2023!

Introduction to Geospatial Machine Learning with SRAI

We’re delighted to announce that our submission to EuroSciPy 2023 has been accepted! We’ll be presenting a tutorial on geospatial machine learning with SRAI and a poster about the SRAI project.

Our PhD scholarship proposal has been accepted for financing by the Unite! project!

Using Large Language Models in the Context of Understanding and Generating Geospatial Language and Data

We’re delighted to announce that the Unite! meta university project will be financing our proposal for a PhD position on the verge of NLP and geospatial data with a focus on large language models and content generation.

We presented a talk at Spatial Data Science Symposium’s workshop on Geography According to ChatGPT

Mapping the Future: Generating Vector Map Layers using ChatGPT and Stable Diffusion for Map Imagery

Kraina AI’s team leader presented a vision talk on large models and map generation at the SDSS workshop.

Paper accepted at GeoAI @ SigSpatial 2022!

highway2vec: representing OpenStreetMap microregions with respect to their road network characteristics

We’re delighted to announce that our submission to GeoAI@SigSpatial 2022 has been accepted! We’ll be presenting a paper on OpenStreetMap region representation learning with respect to their road network characteristics.

Paper accepted at ARIC @ SigSpatial 2021!

Transfer Learning Approach to Bicycle-sharing Systems’ Station Location Planning Using OpenStreetMap Data

We’re delighted to announce that our submission to the 4th ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities (ARIC) has been accepted! We’ll be presenting a paper on effective geographic transfer learning using OpenStreetMap region features for bike station location predictions.

Paper accepted at ARIC @ SigSpatial 2021!

Transfer Learning Approach to Bicycle-sharing Systems’ Station Location Planning Using OpenStreetMap Data

We’re delighted to announce that our submission to the 4th ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities (ARIC) has been accepted! We’ll be presenting a paper on effective geographic transfer learning using OpenStreetMap region features for bike station location predictions.

Paper accepted at GeoSearch @ SigSpatial 2021!

hex2vec - Context-Aware Embedding H3 Hexagons with OpenStreetMap Tags

We’re delighted to announce that our submission to GeoSearch @ SigSpatial 2021 has been accepted! We’ll be presenting a paper on OpenStreetMap region representation learning with respect to public transport quality offering.

Paper accepted at GeoAI @ SigSpatial 2021!

hex2vec - Context-Aware Embedding H3 Hexagons with OpenStreetMap Tags

We’re delighted to announce that our submission to SigSpatial 2021 has been accepted! We’ll be presenting a paper on OpenStreetMap region representation learning with respect to their urban and POI characteristics.