This paper argues that an integrated geospatial approach based on methods of machine learning is well suited to this purpose. Recognizing the intrinsic wickedness of traffic safety issues, such approach is used to unravel the complexity of traffic crash severity on highway corridors as an example ...
This research aims to delineate GWP zones using application of machine learning (ML) models namely random forest (RF), support-vector machine (SVM) and artificial neural network (ANN) with geospatial technique to integrate hydrogeological/ geo-environmental groundwater conditioning variables. A total ...
Combining geospatial data with machine learning in projects that support disaster response, humanitarian action and conservation efforts.
Combining geospatial data with machine learning in projects that support disaster response, humanitarian action and conservation efforts.
kaggle-advertised-salaries - Predicting job salaries from ads - a Kaggle competition. kaggle amazon - Amazon access control challenge. kaggle-bestbuy_big - Code for the Best Buy competition at Kaggle. kaggle-bestbuy_small Kaggle Dogs vs. Cats - Code for Kaggle Dogs vs. Cats competition. Kaggle...
Welcome to the comprehensive course on AI, Deep Learning, and Machine Learning in Geospatial Analysis using Python and R. Geospatial data, from satellite imagery to GPS data, holds immense potential for understanding and solving real-world problems. In this course, we delve into the powerful inter...
In this work, we develop a machine-learning-based framework combining widely-available multi-modal data including street view images, road networks, and building maps to predict the geospatial map of distribution grids. Its performance is extensively evaluated across the test areas in both California...
Maxar GeoHIVE® enables organizations, small and large, to identify and verify change at scale quickly with advanced machine learning & geospatial experts.
Our news reporters obtained a quote from the research from Dalhousie University: "To detect such occurrences with supervised learning methods the AIS messages must be manually annotated, which can be a demanding process. Therefore, unsupervised methods are used to identify anomalous traffic patterns ...
Combining geospatial data with machine learning in projects that support disaster response, humanitarian action and conservation efforts.