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.
AI to Predict Yield in Aeroponics
Python data pipeline to acquire, clean, and calculate vegetation indices from Sentinel-2 satellite image. Package is available only for our clients.
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
METADATA-FARMER ASSISTANCE WEBAPP | AI & ML
ECE471 Final Project: Pixel-Wise Crop Yield Prediction from County-Wise Labels
AKFruitYield: AK_SW_BENCHMARKER Azure Kinect Size Estimation & Weight Prediction Benchmarker.
Django application for predicting Rice Crop Yield using Random Forest algorithm.
Using an efficient Graph-Based approach, analyze a collection of Arecanut images to determine the quantity of Arecanuts in each cluster. Then, extrapolate the total number of nuts within the entire yield based on the individual counts from each cluster.
Simple raw materials and transformations yield calculation symfony 5 app
An Excel based interface for the soybean model GLYCIM
Morgan Stanley's Quant Challenge Qualifier Competition
With the given a set of images of the Arecanuts yield, count the number of Arecanuts available in each bunch and based on the count obtained from each bunch, estimate the total number of nuts available from the yield using efficient Graph Based approach.
This repository provides Lastools and R based scripts for 3D LiDAR data processing and imputation modelling for yield prediction at plot and individual tree levels
Source code for a soybean simulation model- GLYCIM
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