[IROS24] Offical Code for "FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework" - Inegrated into Nerfstudio

Set of Machine Learning Algorithms developed with the aim of determining health states of different types of crops

Advancement of UAV, deep Learning and cutting edged technologies and papers in Precision Agriculture.

Neural-Kalman GNSS/INS Navigation for Precision Agriculture

This GitHub repo contains the code for a precision agriculture app built with Python-Django, and Typescript-Angular. The whole web app is designed to help farmers manage their dairy and poultry farms by making data-driven decisions for their business. In this repo, you'll find the code for the dairy and poultry franchises

Precision Agriculture based ML and DL project (local host deployment) which have features of crop recommendation, fertilizer recommendation and pesticide recommendation.

Bovine Heat Detection and Analysis Tool (BovHEAT) - Automated heat detection and analysis tool for "SCR Heatime" cow activity monitoring data.

Arduino Library for Arduino Edge Control

Autonomous UAV guidance on precision agriculture plantations based on crop row detection algorithm.

A Lightweight Deep Learning Model for Automated Pest Detection on Mobile

Official Repository for CWD30 Dataset

TerrAvion API example

An Android APP to record precision areas for farming purposes

🥔 Supplementary material for Parent, S.-É., Leblanc, M., Parent, A.-C., Coulibali, Z. and Parent, L.E. (2017). Site-specific multilevel modeling of potato response to nitrogen fertilization. DOI: 10.3389/fenvs.2017.00081

Low-cost sensor node device using solar energy and a sx1276 LoRa transmitter for a Wireless Sensor Network.

Precio is a comprehensive application designed to assist modern farmers in optimizing their agricultural operations by incorporating precision farming practices.

BigDataGrapes H2020 project

Deep Learning-based Early Weed Segmentation using Motion Blurred UAV Images of Sorghum Fields

Revoltionizing Precision Agriculture with Real-Time data integration and analysis. Enhancing crop yield, sustainability, and farmer independence using IoT, Cloud and AI.

Yellow Sticky Traps Dataset with improved annotations. Based on: "Raw data from Yellow Sticky Traps with insects for training of deep learning Convolutional Neural Network for object detection" by A.T. Nieuwenhuizen et. al.