TheGeoICT
Anything Earth Observation Related.
Учет различий в инструментах с помощью фундаментальных моделей наблюдения за Землей (EOFM) | Райа...
Глава 1 | Картографирование рисовых плантаций в Бутане в 2021 году с использованием глубокого обу...
Советы по видеообучению книги «Глубокое обучение»
Составление графика NEPA: запрограммирование геоинтеллектуального будущего федеральных разрешений...
Внедрение векторного поиска и не только с помощью BigQuery и Earth Engine | Geo for Good 2025
АВТОР: Community Research Earth Digital Intelligence Twin | Доктор «DJ» Ганье | Руководитель MILE...
Pipeline Data Agent - Pipeline Analytics with Google Agent Development Kit (ADK)
Using ArcGIS Pro as an On-Ramp to Deep Learning in Earth Observation | Emil Cherrington
Transforming Flood Analysis: Hydro-SAR Next Generations and Journey to KTM, Nepal | Arif Albayrak
Geospatial AI Analyst Agent on the Next-Gen Geospatial Data Infrastructure | Nika Co | Lawrence Xiao
They Come in Peace?How helpful, skilled, and/or threatening can LLM be in Remote Sensing?
Breaking Earth Observation Barriers: From Data Silos to Intelligent, Reliable Discovery | Element 84
Using Earth Engine-BigQuery for Vector Search using Clay Embeddings
Desert Locust Breeding Ground Prediction in Africa using Geo-Foundational Model (Prithvi)
Evaluating EOFMs for Impact - Current Trends and Future Directions | Kyle Woodward | SIG
AI Hydrology In-practice: Lessons from 6 years of operational streamflow forecasting: Alden Sampson
Clay - Open Foundation Model of Earth: Soumya Ranjan
Using Computer Vision, Machine Learning and Artificial Intelligence with Earth Observation -Dr Modou
Deep Learning-Driven Insights into Flood Extent and River Flow in the HKH Region
Towards Digital Twin: Introduction to Foundation Models for Geoscience -- Dr Sujit Roy, NASA IMPACT
A Phenology-guided Bayesian-CNN (PB-CNN) Framework for Yield Estimation and Uncertainty Analysis
FlexibleNet: A New Lightweight CNN Model for Estimating Carbon Sequestration Qualitatively
Using Machine Learning & Deep Learning to Improve Trace Gas and Particulate Matter (PM) Estimations
Presto: Lightweight, Pretrained Transformers for Remote Sensing Timeseries | Gabriel Tseng | Harvest
Best Practices for Creating a Land Cover Map Using Machine Learning - Micky Maganini
Earth Index - Envisioning the future Foundation Model powered Geospatial Tech Stack: Dr Ben Strong
High Resolution Tree Counting and Height Mapping using Transformers and Foundational Model