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portada AI-Driven Soil Classification: Faster R-CNN Deep Learning Approach
Type
Physical Book
Publisher
Author
Language
English
Pages
56
Format
Paperback
Dimensions
22.9x15.2x0.3 cm
ISBN13
9786208454180

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

Mondal, Saptarshi; Roy, Rupsha (Author) · LAP Lambert Academic Publishing · Paperback

AI-Driven Soil Classification: Faster R-CNN Deep Learning Approach - Mondal, Saptarshi; Roy, Rupsha

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

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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