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Home > Mathematics and Science Textbooks > Biology, life sciences > Botany and plant sciences > AI-Driven Soil Classification: Faster R-CNN Deep Learning Approach
AI-Driven Soil Classification: Faster R-CNN Deep Learning Approach

AI-Driven Soil Classification: Faster R-CNN Deep Learning Approach


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About the Book

This book presents an advanced deep learning solution for soil classification using Faster R-CNN, achieving 99.94% accuracy. It leverages image-based analysis to accurately classify multiple soil types, including Black, Alluvial, Loamy, and Red soils. The approach integrates image preprocessing, region proposal networks, and robust neural feature extraction to ensure high detection and classification performance. Visual outputs, including bar charts, scatter plots, and line graphs, illustrate predictive accuracy and confidence scores, enabling a better understanding of model performance. Designed for applications in precision agriculture and environmental science, this work reduces dependency on traditional lab-based soil analysis and speeds up decision-making in soil management. By merging AI-driven techniques with practical agricultural needs, this research sets a benchmark for soil analytics and highlights how deep learning can transform sustainable farming and resource optimization.


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Product Details
  • ISBN-13: 9786208454180
  • Publisher: Lap Lambert Academic Publishing
  • Publisher Imprint: LAP LAMBERT Academic Publishing
  • Height: 229 mm
  • No of Pages: 56
  • Returnable: N
  • Sub Title: Faster R-CNN Deep Learning Approach
  • Width: 152 mm
  • ISBN-10: 6208454182
  • Publisher Date: 06 Aug 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 3 mm
  • Weight: 141 gr


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AI-Driven Soil Classification: Faster R-CNN Deep Learning Approach
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