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    <title>Object-Based Image Analysis on João Gonçalves</title>
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    <description>Recent content in Object-Based Image Analysis on João Gonçalves</description>
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    <copyright>&amp;copy; 2026</copyright>
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      <title>SegOptim</title>
      <link>http://joaogoncalves.cc/software/segoptim/</link>
      <pubDate>Sun, 01 Dec 2024 00:00:00 +0000</pubDate>
      
      <guid>http://joaogoncalves.cc/software/segoptim/</guid>
      <description>SegOptim SegOptim is an R package for object-based image analysis (OBIA). It allows to run, compare and optimize multiple image segmentation algorithms in the context of supervised classification. It also allows to perform unsupervised classification with several different methods and compare them through internal clustering metrics.
For more details about installation and how to use the package go to the tutorial here. Check also the paper describing the package functionalities here.</description>
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      <title>rsegm</title>
      <link>http://joaogoncalves.cc/software/rsegm/</link>
      <pubDate>Sun, 01 Dec 2024 00:00:00 +0000</pubDate>
      
      <guid>http://joaogoncalves.cc/software/rsegm/</guid>
      <description>rsegm The rsegm package provides scalable, high-performance tools for geospatial image segmentation built on top of terra, Rcpp, and modern block-wise / tiled processing strategies. It is designed for object-based image analysis (OBIA) workflows on large raster datasets, including satellite and aerial imagery. The core focus is on producing spatially coherent, integer-labeled segment rasters that integrate cleanly with downstream raster and vector analysis in R.
Key Features  Graph-based and hybrid segmentation algorithms: Includes Fast Felzenszwalb-Huttenlocher (FH) graph-based segmentation, Hybrid FH + region-level Mean Shift segmentation, Baatz-Schäpe multi-resolution, Fast Baatz-Schäpe multi-resolution, and SEEDS.</description>
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