ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
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Updated
May 7, 2023 - PHP
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
codes for RS paper: Rice-Yield Prediction with Multi-Temporal Sentinel-2 Data and 3D CNN: A Case Study in Nepal
The Crop Management System is a machine learning-based project designed to provide predictions and recommendations for farmers.
Python data pipeline to acquire, clean, and calculate vegetation indices from Sentinel-2 satellite image. Package is available only for our clients.
Reinforcement Learning for Improving Chemical Reaction Performance
AI to Predict Yield in Aeroponics
AK_VIDEO_ANALYZER that analyses videos on which to automatically detect apples, estimate their size and predict yield at the plot or per hectare scale using the appropriate simulated algorithms.
Goal of this project was to predict beef carcass 22 yield parameters using image analysis. The code (written in MATLAB, Python) for image processing, feature extraction and multivariate modelling is found in this repository
ECE471 Final Project: Pixel-Wise Crop Yield Prediction from County-Wise Labels
METADATA-FARMER ASSISTANCE WEBAPP | AI & ML
ML solutions and other API based features to support Agriculture and Farmers. Goto Wiki or click on below link for Project Report.
Neural network model for predicting yield per unit area based on the location
Système professionnel de yield management touristique. Basé sur 8+ années d'expérience terrain gérant €15M+ de contrats avec Oberoi, Mercure, TBH Hotels, Hilton. +23% CA, +580K€ profit.
AKFruitYield: AK_SW_BENCHMARKER Azure Kinect Size Estimation & Weight Prediction Benchmarker.
Django application for predicting Rice Crop Yield using Random Forest algorithm.
Morgan Stanley's Quant Challenge Qualifier Competition
An AI-based system that recommends crops, predicts yield and diseases, and provides irrigation guidance using real-time weather and soil data.
The project aims to create a centralized database of farmers with digital profiles that include all their relevant details. Additionally, the system features an alert system for new schemes and subsidies, as well as a machine learning-based crop recommendation system and disease detection with fertilizer suggestions.
Simple raw materials and transformations yield calculation symfony 5 app
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