The GeoDjango extension provides Django model fields for OGC geometries and raster data which are utilized in django-raster to provide a high-level interface for storing raster data. They had a clean interface to GDAL (Geospatial Data Abstraction Library, the de facto standard library for handling geospatial data formats) for storing raster imagery and performing tile serving. Since Resonant GeoData uses Django with PostGIS for its backing database, we were thrilled to find the GeoDjango contrib module and django-raster Django app. Visualizing a raster image dataset on an interactive slippy map. We also wanted users to be able to perform this analysis within the web application as they are sorting through the search results from Resonant GeoData’s catalog API.
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We wanted to enable users of Resonant GeoData to interactively visualize satellite imagery in a dynamic manner (rescaling, color mapping, etc.).This allows them to gain insights into the data for quality control analysis and to find the right dataset to download for processing. While Resonant GeoData is a broader platform of geospatial data services in Django, in this post, we will focus on the path we took to create a standalone library to dynamically serve tiles with Django from large, remotely-hosted images for visualization in web browsers. Resonant GeoData not only indexes these data into a searchable catalog but also dynamically serves the data to our customers for processing and visualization.
Visualizing Geospatial Images in Your Web-BrowserĪ core part of Kitware’s Resonant GeoData platform is working to ingest cloud-hosted geospatial and georeferenced datasets – namely satellite imagery. Read on for the story and motivation behind django-large-image. It provides Django projects with a dynamic tile server preventing the need for preprocessing large images into tile sets or deploying an external tiling service for viewing images interactively on a slippy-map interface. It is built on django-rest-framework’s viewset class interface and Kitware’s large-image package. django-large-image is a Django app with an extensible interface for building web applications focused on dynamic tile serving of large image formats. We debuted django-large-image to the world during the 2022 Cloud-Native Geospatial Outreach Event with a video recording and slides. We are excited to introduce a new tool from this effort for dynamic tile serving of geospatial and medical images: django-large-image. Promising avenues for future research in this rapidly advancing field, whichĬould bring us closer to understanding the essence of intelligence.Adapting our large-image toolkit to Django for solving geospatial and medical image challenges on the webĪt Kitware, we have been building a suite of geospatial data cataloging, visualization, and analysis tools in Django under the Resonant GeoData brand for the past two years.
Moreover, we delve into the potentialĪdvantages and challenges accompanying this approach. Of more biologically plausible mechanisms, such as synaptic plasticity, toĮnhance these networks' capabilities.
Representations in artificial neural networks. Paper presents a comprehensive review of current brain-inspired learning Those of the biological brain, particularly concerning learning processes. There exist fundamental differences between ANNs' operating mechanisms and Including image and speech generation, game playing, and robotics. Machine learning, achieving remarkable success across diverse domains,
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Download a PDF of the paper titled Brain-inspired learning in artificial neural networks: a review, by Samuel Schmidgall and 6 other authors Download PDF Abstract: Artificial neural networks (ANNs) have emerged as an essential tool in
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