Face Recognition & AI Based Smart Attendance Monitoring System.

Related tags

Deep LearningSAMS
Overview

In today’s generation, authentication is one of the biggest problems in our society. So, one of the most known techniques used for authentication is human face recognition, which is also known as HFR. For example- nowadays we can unlock our phone using the face recognition feature. In the existing system, Our lecturers take attendance manually which is somewhat time-consuming and old school type. So, our Artificial Intelligence-based attendance monitoring system will be capturing the faces of every student in a class during attendance and the result will get stored in the database automatically. There will be no extra Radio frequency Identification card, people need to carry anymore and this system will be the most authentic system of taking attendance. The system stores the faces that are detected and automatically uploads the attendance to the database. Using This process our primary goal is to help lecturers as well as students to track and manage student's attendance and absenteeism.

Owner
Sagar Saha
Software Engineer @Nagarro.
Sagar Saha
TrackTech: Real-time tracking of subjects and objects on multiple cameras

TrackTech: Real-time tracking of subjects and objects on multiple cameras This project is part of the 2021 spring bachelor final project of the Bachel

5 Jun 17, 2022
The final project of "Applying AI to 3D Medical Imaging Data" from "AI for Healthcare" nanodegree - Udacity.

Quantifying Hippocampus Volume for Alzheimer's Progression Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that result

Omar Laham 1 Jan 14, 2022
Simple SN-GAN to generate CryptoPunks

CryptoPunks GAN Simple SN-GAN to generate CryptoPunks. Neural network architecture and training code has been modified from the PyTorch DCGAN example.

Teddy Koker 66 Dec 15, 2022
Context Axial Reverse Attention Network for Small Medical Objects Segmentation

CaraNet: Context Axial Reverse Attention Network for Small Medical Objects Segmentation This repository contains the implementation of a novel attenti

401 Dec 23, 2022
Diverse Image Generation via Self-Conditioned GANs

Diverse Image Generation via Self-Conditioned GANs Project | Paper Diverse Image Generation via Self-Conditioned GANs Steven Liu, Tongzhou Wang, David

Steven Liu 147 Dec 03, 2022
A curated list of long-tailed recognition resources.

Awesome Long-tailed Recognition A curated list of long-tailed recognition and related resources. Please feel free to pull requests or open an issue to

Zhiwei ZHANG 542 Jan 01, 2023
Neuron Merging: Compensating for Pruned Neurons (NeurIPS 2020)

Neuron Merging: Compensating for Pruned Neurons Pytorch implementation of Neuron Merging: Compensating for Pruned Neurons, accepted at 34th Conference

Woojeong Kim 33 Dec 30, 2022
Pure python implementation reverse-mode automatic differentiation

MiniGrad A minimal implementation of reverse-mode automatic differentiation (a.k.a. autograd / backpropagation) in pure Python. Inspired by Andrej Kar

Kenny Song 76 Sep 12, 2022
render sprites into your desktop environment as shaped windows using GTK

spritegtk render static or animated sprites into your desktop environment as dynamic shaped windows using GTK requires pycairo and PYGobject: pip inst

hermit 20 Oct 27, 2022
PyTorch implementations of the paper: "Learning Independent Instance Maps for Crowd Localization"

IIM - Crowd Localization This repo is the official implementation of paper: Learning Independent Instance Maps for Crowd Localization. The code is dev

tao han 91 Nov 10, 2022
TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video

TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video Timely handgun detection is a cr

Mario Duran-Vega 18 Dec 26, 2022
Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)

Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train

Jongheon Jeong 174 Dec 29, 2022
Evaluating saliency methods on artificial data with different background types

Evaluating saliency methods on artificial data with different background types This repository contains the relevant code for the MedNeurips 2021 subm

2 Jul 05, 2022
A Topic Modeling toolbox

Topik A Topic Modeling toolbox. Introduction The aim of topik is to provide a full suite and high-level interface for anyone interested in applying to

Anaconda, Inc. (formerly Continuum Analytics, Inc.) 93 Dec 01, 2022
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.

Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.

Nikolas Petrou 1 Jan 13, 2022
[NeurIPS 2021] "Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems"

Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems Introduction Multi-agent control i

VITA 6 May 05, 2022
Code for Fold2Seq paper from ICML 2021

[ICML2021] Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design Environment file: environment.yml Data and Feat

International Business Machines 43 Dec 04, 2022
Exploration & Research into cross-domain MEV. Initial focus on ETH/POLYGON.

xMEV, an apt exploration This is a small exploration on the xMEV opportunities between Polygon and Ethereum. It's a data analysis exercise on a few pa

odyslam.eth 7 Oct 18, 2022
PyTorch implementation of CVPR'18 - Perturbative Neural Networks

This is an attempt to reproduce results in Perturbative Neural Networks paper. See original repo for details.

Michael Klachko 57 May 14, 2021
Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF shows significant improvements over baseline fine-tuning without data filtration.

Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho

4 Jul 28, 2022