This project is for the Identification of Iris flower species is presented
-
Updated
Sep 17, 2020 - Jupyter Notebook
This project is for the Identification of Iris flower species is presented
Iris landmarks localization.
Official Dynamic Graph Representation PyTorch implement for iris/face recognition
Iris recognition program according to John Daugman's papers
Yet Another Platform for Iris Recognition
Biometric system that can recognize users using photos of their irides. Based on ResNet50.
Iris recognition is a reliable and accurate biometric identification system for user authentication. It is used for capturing an image of an individual’s eye. The performance of iris recognition systems is measured using segmentation. Segmentation is used to localize the correct iris region in the particular portion of an eye and it should be do…
Triplet loss based iris recognition
👁️ A Biometric Authentication system using Iris. Enrollment and Authentication Modules. End to End, Iris Segmentation Free using DCNNs, Accuracy of 93.15% 👁️
Series of image recognition algorithms that can diagnose diseases by analysing a picture of the iris of the person
A Resource-Efficient Embedded Iris Recognition System Using Fully Convolutional Networks
This is an Iris Recognition mobile app. That used a deep learning model infernce to do the authentication based on the eyes Iris.
Iris Segmentation Code Based on the Generalized Structure Tensor (GST)
Iris Segmentation Groundtruth Database
IrisWise is a machine learning application for predicting Iris flower species. Built with Streamlit, this app provides a user-friendly interface to input flower measurements and receive predictions using various models, including K-Nearest Neighbors, (Random Forest, SVM, and Logistic Regression) **(Working On It...)**.
Iris Recognition With Tensorflow And MMU Dataset
Add a description, image, and links to the iris-recognition topic page so that developers can more easily learn about it.
To associate your repository with the iris-recognition topic, visit your repo's landing page and select "manage topics."