Dataset used in "PlantDoc: A Dataset for Visual Plant Disease Detection" accepted in CODS-COMAD 2020

Training and evaluating state-of-the-art deep learning CNN architectures for plant disease classification task.

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Predictive model for cannabis sickness

Plant Disease Detection using ML model and Android App

PlantDreamer: Achieving Realistic 3D Plant Models with Diffusion-Guided Gaussian Splatting [CVPPA: ICCVW 2025]

Plant Disease Detection

Dataset Analysis & CNN Models Optimization for Plant Disease Classification.

Implementation Of The Methods Used In The Paper Titled- "Plant Disease Detection Using Machine Learning". Done As Part Of the Application Screening Activity For University's Computer Engineering Department Research Group

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Repo for the Bill & Melinda Gates Foundation DataDive

A Plant Disease Detector App based on Nested Transfer Learning

Plant disease detector and fertilizer recommendation system

An application for detecting diseases in plants.

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A plant database for keeping track of all your home-grown stuff using the python web framework Django

Transforming agriculture with AI: Explore our GitHub for advanced plant disease detection. Utilizing top CNN models, we empower farmers with early diagnosis tools. Access notebooks, datasets, and a user-friendly web app. Join us in revolutionizing farming for a sustainable future

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植物识别（含算法）

Convolutional neural network models were developed to perform plant disease detection and diagnosis using simple leaves images of healthy and diseased plants, through deep learning methodologies. Training of the models was performed with the use of an open database of 19,721 images, containing different plants in a set of 15 distinct classes of [plant, disease] combinations, including healthy plants. Several model architectures were trained, with the best performance reaching a 93.6% success rate in identifying the corresponding [plant, disease] combination (or healthy plant). The significantly high success rate makes the model a very useful advisory or early warning tool, and an approach that could be further expanded to support an integrated plant disease identification system to operate in real cultivation conditions.

Training on Plant Disease Classification for AICTE Internship Cycle 4

农作物病害检测系统

Plant Data Service at GOAT:Hack

This repo contains code for the LeafDiseaseClassifier model which is deployed as a REST API on Heroku Webserver. This API is developed using the Flask framework.

PlantVillage plant disease split into test and train dataset

Transfer learning efficientNet to classification disease on plants. Build web application with React and FastAPI