Unsupervised Classification | Land Use & Land Cover Map in ArcMap
Unsupervised Classification | Land Use & Land Cover Map in ArcMap
About this Video
Unsupervised image classification is a branch of computer vision and machine learning where algorithms are used to automatically group similar images into distinct categories or clusters without the need for labeled training data. Unlike supervised learning, where algorithms learn from labeled examples, unsupervised image classification relies solely on the inherent patterns and relationships present within the images themselves.
The primary goal of unsupervised image classification is to discover underlying structures and patterns within a collection of images. This can be particularly useful in scenarios where obtaining labeled data is challenging, expensive, or time-consuming. Unsupervised techniques can help researchers and practitioners gain insights, identify trends, and organize large volumes of visual data efficiently.
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3️⃣ QGIS Basics Tutorials: https://bit.ly/3Oljo95
4️⃣ ArcMap Basics Tutorials: https://bit.ly/3DoAopy
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6️⃣ Hydrological Analysis: https://bit.ly/472LGgY
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Queries Solved by this video:
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