A coolection of tools for organizing directories, specifically converting the Labeled Faces of the Wild (cropped) to a common standard.

Face Recognition Implementation using PCA, eigenfaces, and SVM

PcaNet, PCA Network, Deep Learning, Face Classification, LFW dataset, SVM

Face Recognition with convolutional neural network (CNN) on Labeled Faces in the Wild (LFW) dataset

A simple colab notebook on validation of face recognition model on LFW test dataset.

Just some implementations of my understanding of Generative models

📚 A collection of ml datasets & corpuses

Final Project Of Computational Intelligence - Fall 2021 - LightGBM, RandomForest and StackingClassifier

Implementation and training of facial identification model on LFW dataset.

Simple application of VGG16 for the recognition of images, obtained from LFW, of a limited number of famous(15) with good performance (greater than 80%)

GAN trained on the preprocessed LFW dataset with an analysis of peculiar generation artifacts.

Autoencoders test from Coursera's Advanced Machine Learning - Intro to Deep Learning course.

A recognition process of images contained in the LFW database http://vis-www.cs.umass.edu/lfw/#download is carried out using two models, one based on the minimum distance between training image records and test and another that is an adaptation of the CNN KERAS model https://keras.io/examples/vision/mnist_convnet/. Both models are complementary.…

🎨 Restore images flawlessly with our Image Inpainting Showcase! Using Convolutional Neural Networks, we revive corrupted parts. Explore code, models, and innovation for visual perfection. Join the AI journey of artistry and magic! 🖼️🔮 #ImageInpainting

Analysing different dimensionality reduction techniques and svm

dog breed classifier based on convnets, using catdog and lfw datasets.

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.

PyTorch implementation of LS-CNN: Characterizing Local Patches at Multiple Scales for Face Recognition

Code for training and parameter tuning of a machine learning model for non-linear aggregation of image denoising estimators using COBRA combined regression strategy. The face images used for training and testing are taken from the Labelled Faces in the Wild (LFW) dataset.

Image Inpainting using Context Encoders