Popular GitHub Repositories for Imageclassification

This is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.

To Detect and Classify Brain Tumors using CNN and ANN as an asset of Deep Learning and to examine the position of the tumor.

Skin Lesion Analysis Towards Melanoma Detection

Image classification using Transfer learning technique. Updated and added mlflow with PyTorch fine-tune tutorial

Simple CNN is a library that can be used to train and infer CNN models by use of PyTorch and ONNX.

Jax, Flax, examples (ImageClassification, SemanticSegmentation, and more...)

Knowledge distillation pytorch lightning template for image classification task

CheckMyCash is an android app that detects indian curency note denomination using image classification.

Machine Learning mod. 2: Deep Learning - UniTN - Prof. Ricci- MSc AIS 2022

这份简短指南介绍如何使用 Python 的 TensorFlow 框架和训练数据来训练模型。其中包含用于分割数据、训练模型、测试模型以及将 .h5/.keras 模型转换为 .tflite 模型的代码。

This repository contains Jupyter Notebooks for image classification tasks using Convolutional Neural Networks (CNNs). The included notebooks demonstrate techniques for classifying images from the CIFAR-10 dataset, handwritten digits using the MNIST dataset, and general CNN architectures.

Animal Prediction is a web application developed using Python and Django that allows users to predict the animal species based on uploaded photos. The application utilizes machine learning algorithms to analyze the image data and provide accurate predictions.

This repository includes of a Multi-Tag (acronyms are Multi-Task and Multi-Output as well) Image Classification on Fashion Products Images dataset on Kaggle using EfficientNetB0 with high accuracies

A machine learning model to classify the gender of a person based on an image of their eye, using a CNN. Dataset includes eye images of males and females. Model is evaluated using accuracy score.

Efficient b7 Training, Transfer Learning

Lung Cancer Classification app with FastAPI and Docker

This project uses an ensemble of CNN, RNN, and VGG16 models to enhance CIFAR-10 image classification accuracy and robustness. By combining multiple architectures, we significantly outperform single-model approaches, achieving superior classification performance.

A deep residual neural network in the fashion of ResNet50, capable of completing image classification tasks efficiently. Manually implemented the core layer blocks.

This project is a handwritten digit classifier built with PyTorch and trained on the MNIST dataset. It uses a Convolutional Neural Network (CNN) to recognize digits from 0 to 9 with high accuracy. The project features a Streamlit web app that allows users to upload their own handwritten digit images and get real-time predictions.

This project builds a Convolutional Neural Network (CNN) to classify landmarks from images. It includes developing a CNN from scratch and enhancing performance with transfer learning (achieving 75% accuracy using ResNet18).