Prediction and Analysis in Neural Networks
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Updated
Jul 1, 2023 - HTML
Prediction and Analysis in Neural Networks
Plant disease detection using images of leaves
Use of computational vision techniques to detect plant diseases
Django Websites For Named Entity Recognition and Relation Extraction, Support by BRIN and Gunadarma
Matura Project Assignment (High School Thesis) of Matyáš Boháček at Gymnázium Jana Keplera, 2022/2023
A Convolutional Neural Network based image classification model to detect disease in plants.
Eggplant biotic stress detection app using CNN
Mini project files for semester 6 (An ML-based project integrated with flutter). The trained model has been deployed on pythonanywhere from anaconda and fetched on flutter application with predicted plant disease with confidence for that class.
Dataset Analysis and CNN Models Optimization for Plant Disease Classification.
Biomedical Plant Disease Gold Standard Corpus Dataset For Relation Extraction From NCBI
AgroGuard is a deep-learning-based application that helps us identify different diseases in plants and provides timely cures.
A tool to scan crops and predict healthy crops, crop rust, or powdery mildews.
Biomedical Plant Disease Gold Standard Corpus Dataset For Named Entity Recognition From NCBI
Classifier build to recognize disease on apple leaves images
Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity
Flutter Application to help plant owners diagnose and treat diseases that may affect their plants.
This is a web app for predicting plant diseases using Convolutional Neural Networks (CNN). The model is trained on the PlantVillage dataset which contains images of healthy and diseased plant leaves. The dataset consists of 38 classes of plant diseases. The model is built using TensorFlow and Keras and trained on Google Colab.
This is a deep learning project in agriculture domain that detect plants diseases
Welcome to the Plant Disease Classifier Deployment repository! This project integrates cutting-edge technologies to develop a sophisticated plant disease classifier. Leveraging TensorFlow for model creation and ReactJS for the web interface, this project offers an innovative solution for identifying plant diseases swiftly and accurately.
Using a pre-trained efficientnet (for experimental purposes) to classifier plant diseases given an image. Plant village challenge dataset.
Add a description, image, and links to the plant-disease topic page so that developers can more easily learn about it.
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