Facial recognition using pretrained VGGFace model to compare faces from images and recognise/match them.
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Updated
Nov 8, 2020 - Jupyter Notebook
Facial recognition using pretrained VGGFace model to compare faces from images and recognise/match them.
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
A containerized facial recognition module based on VGG ResNet-50 architecture
Used VGGFace and Resnet50 model we extract features from the photos of the celebrities. It predicts the similar matching Bollywood celeb based on cosine similarity of the pictures.
Facial Recognition with VGG Face in Tensorflow 2.0
RealTime Emotion Recognizer for Machine Learning Study Jam's demo
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.
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.
using Facial and GeoLocation verification
Exploring the relationship between facial features and first name using Stanford's Names100 Dataset
Face Identification In Artwork
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.
A facial expression recognition project with VGGFace Transfer Learning Model on the Nigerian Static Facial Expression (NISFE) dataset
Using MTCNN and VggFace, created a webApp which tells your look alike Bollywood celebrity
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.
Using CNNs to perform facial expression recognition and analysing TED talks to gain insights.
DeepFace Library lets you recognize and analyze faces quickly with models like VGGFace and Facenet.
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.
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