plantvillage

A ResNet50-DCBAM deep learning framework for plant disease classification using the PlantVillage dataset with reproducible training and evaluation pipelines.

Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".

Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".

It is an application that leverages benefits of CNNs and predicts the disease of an infected plant by examining the image of the infected leaf. It also provides the organic method to prevent the disease.

Code in Torch for PlantVillage challenge: https://www.crowdai.org/challenges/1

A plant disease classification system using convolutional neural networks (CNNs) to identify healthy and diseased plant leaves from images, with interactive visualization through Gradio for real-time predictions and feature map analysis.

Plant disease detection on PlantVillage dataset using EfficientNetV2-B0

Detection of disease type in tomato leaves using Alexnet

InovaPlant AI is an advanced agritech diagnostic engine. It uses a Dual-Model (Ensemble Learning) approach with TensorFlow & Flask to detect 38 plant diseases with high accuracy, providing instant treatment reports.

Robustness of ResNet-50, EfficientNet-B0, ConvNeXt-Tiny & ViT-B/16 to image corruption in plant disease diagnosis (PlantVillage, ImageNet-C protocol)

Plant disease classification achieving 99.54% accuracy using EfficientNet-B3 with two-phase fine-tuning, CutMix/MixUp augmentation, and Test-Time Augmentation. Classifies 39 disease types across 14 crop species from leaf images.

PyTorch computer vision project for plant disease detection using ResNet18 transfer learning, class-weighted training, and F1-score based evaluation.

This repository contains an implementation of a CNN which predicts the disease that a tomato plant has based on a picture of one of its leaves. Images were obtained from the PlantVillage dataset.

Deep Learning (MobileNetV2 & PyTorch) powered Plant Leaf Disease Detection Web App with %99.28 Validation Accuracy and Active Learning loop. 🌿

Plant disease screening demo with PyTorch, Flask, and a local PlantVillage baseline.

SOTA 99.47% accuracy on PlantVillage dataset using PyTorch. A deep dive into fine-tuning ResNet50 for plant disease classification.

Plant Disease Detection Web Application using CNN BioShield AI (MobileNetV2 & EfficientNetB0) with Flask and Transfer Learning.

Leakage-free deep-learning framework for apple-leaf disease detection and classification, with honest cross-dataset evaluation (zero-shot vs. cross-validation), YOLOv11 detection, and a data-efficiency study showing that leakage-free pre-training cuts field-data needs.

AI-powered multi-crop plant disease detection app using PyTorch ResNet18 and Streamlit. Classifies 34 plant leaf disease and healthy classes with treatment guidance.

Tomato leaf disease classifier using EfficientNetB0 transfer learning — 10 classes, 92.5% accuracy, TFLite export ready.