EVERYTHING YOU NEED FOR DATA SCIENCE.

Model to recognize celebrities using a face matching algorithm.

Utilizing the DeepFace Library, informed by a dataset of 4M images across 4K identities curated by Facebook researchers, My 'Two Faces✌🏻' project gauges facial similarity with precision.

VGGFace implementation with Keras Framework

Dive into the world of computer vision! Our Image Classification from Video project uses advanced techniques to identify faces in images and videos. Explore video processing, face extraction, and deep learning magic. Join the adventure now! 👩‍💻📸"

using Facial and GeoLocation verification

This is my capstone project that was completed as part of the General Assembly Data Science Immersive curriculum. I conceptualized the idea, executed the project and developed a prototype for predicting success in the South Korean drama industry based on face image. This serves as a proof-of-concept which can definitely be developed further.

This project is aimed at developing a deep learning system that can detect and recognize people who look identical to Bollywood actors. It will use facial features as the basis of comparison for detecting similar features between two people. This system could be used in various applications such as security systems, entertainment platforms, etc.

ML model for grouping similar faces using cutting-edge deep learning and computer vision techniques. Custom dataset of 300 images captures comprehensive facial variations. Siamese network outperforms Face-Net, delivering reliable clustering results.

A containerized facial recognition module based on VGG ResNet-50 architecture

Doing attendance of whole classroom with few shots using Python's Flask framework. Feature extraction of detected faces by mtcnn done by fine tuning VVGFace on siamese network.

Data and code for an AI model that predicts remaining lifespan (how many years of life a person has left) solely from a facial image

Using CNNs to perform facial expression recognition and analysing TED talks to gain insights.

A facial expression recognition project with VGGFace Transfer Learning Model on the Nigerian Static Facial Expression (NISFE) dataset

Face Detection, verification and recognition in Near real time on CPU brewing with all the SOTA all over

Facial Recognition with VGG Face in Tensorflow 2.0

DeepFace Library lets you recognize and analyze faces quickly with models like VGGFace and Facenet.

A flask app to give a demo of Facial Recognition - Deployed with Live Demo.

The project consists in the development of an application for the recognition of one-dimensional signals (audio), two-dimensional signals (images) and retrieval of the 10 images most similar to a given query.