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

Offline plant disease diagnosis with MobileNetV3, TensorFlow Lite, and Flutter for field-ready edge AI inference.

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.

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.

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

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

Deep Learning based Crop Disease Detection using ResNet18, PyTorch and Flask

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

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.

Al-based plant disease detection system using deep learning, providing real-time identification and remedy suggestions for crop health management.

CNN image classifier for 38 plant disease classes across 14 species — ResNet34 transfer learning | BE ISE, BNMIT

Deep learning project using Convolutional Neural Network with Classification.