Solutions to kaggle competition-Pneumothorax detection
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Updated
May 23, 2020 - Jupyter Notebook
Solutions to kaggle competition-Pneumothorax detection
Repo for the "APTOS 2019 Blindness Detection" competition on Kaggle, to share my approach to solving the problem.
Leaf disease classification on kaggle
Efficient b7 Training, Transfer Learning
Brain tumor Detection and Classification using Magnetic Resonance Images
Using a CNN to make a facial emotion recognition model and comparing its performance to other transfer layer architectures.
I'm developing an app named BarkRescue, which includes project code, app functionalities, and system architecture. Additionally, I've written three detailed blogs on EfficientNet, YOLOv5, and MobileNet-v2, focusing on their architecture and workings before integrating these models into my project.
Welcome to the repository of our garbage classification project! We have developed a model using PyTorch and EfficientNet-B4 that classifies garbage into twelve different types. The model has achieved an impressive accuracy of 98.45%.
A binary classification using Convolution Neural Network (CNN, or ConvNet) model.
Reteaua neuronala CitNet
One-stage and two-stage face detection models
This project aims to improve the performance of the classification algorithm by implementing state-of-the-art model: EfficientNet in place of VGG-16.
All my Python code used for the Kaggle HuBMAP Semantic Segmentation competition
Image Scene Classification Model for TensorFlow Hub
Project 7 of the course "Specialization Data Science" that updated to the app
MaizeFolioID is an image recognition model trained to predict the presence of foliar diseases in maize leaves.
An end-to-end CNN Image Classification Model which can identify over 100 food classes trained on the Food-101 dataset.
This repository contains the code of the paper Multi-class classification of brain tumor types from MR Images using EfficientNets
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