An open-source library for geotechnical engineering analysis and modeling.
Soil Type Classification Through Image Processing and Machine Learning This project is in development process for our Thesis Project.
A software that classifies type of soil based on its physical properties using CNN. Outputs soil information and amendment for soil improvment.
• Designed a classification model with 5 classes and 98% testing accuracy using a Convolutional Neural Network. • Applied Data Augmentation and reduced validation losses by 30% by applying MobileNetV2 Architecture.
An application for Farmers to recommend them the best types of crops which can be cultivated on a certain piece of land using Soil Image.
Server code for the Agro-Companion website, featuring Flask-based services for deep learning-driven soil classification and fuzzy logic-based crop recommendation
Computer Vision + AI. Poisonous Plant and Soil Type Detection
Quarto version of the World Reference Base for Soil Resources, 4th Edition - https://obrl-soil.github.io/wrbsoil2022/
Agro companion is a soil classification, crop recommendation and crop information website. It helps identify seven types of soils, recommend 20+ crop based on specific factors and also help search information required to grow them.
The New Zealand Soil Classification, Draft 4th Edition
Desarollo movido a https://github.com/ppizarror/granulometria-gui
Soil classification (7 soils) dataset for the paper published in Engineering Applications of Artificial Intelligence: "An advanced artificial intelligence framework integrating ensembled convolutional neural networks and Vision Transformers for precise soil classification with adaptive fuzzy logic-based crop recommendations"
Soil classification using deep learning on image data. Trained a model to classify soil images into Alluvial, Black, Clay, and Red soil categories using PyTorch and GPU acceleration. Achieved high accuracy of 1.000 in a Kaggle competition.
Design and training of artificial intelligence for soil classification using satellite images (ST2 2023 Project)
Working repository for the code of the investigation of minimum soil sample masses
soilDT: the soil classification app
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