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.
Face Recognition & AI Based Smart Attendance Monitoring System.
Overview
基于Pytorch实现优秀的自然图像分割框架!(包括FCN、U-Net和Deeplab)
语义分割学习实验-基于VOC数据集 usage: 下载VOC数据集,将JPEGImages SegmentationClass两个文件夹放入到data文件夹下。 终端切换到目标目录,运行python train.py -h查看训练 (torch)
28 Dec 21, 2022
A framework for Quantification written in Python
QuaPy QuaPy is an open source framework for quantification (a.k.a. supervised prevalence estimation, or learning to quantify) written in Python. QuaPy
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
Source code for paper: Knowledge Inheritance for Pre-trained Language Models
Knowledge-Inheritance Source code paper: Knowledge Inheritance for Pre-trained Language Models (preprint). The trained model parameters (in Fairseq fo
Implementation of Bagging and AdaBoost Algorithm
Bagging-and-AdaBoost Implementation of Bagging and AdaBoost Algorithm Dataset Red Wine Quality Data Sets For simplicity, we will have 2 classes of win
COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models
COVID-ViT COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models This code is to response to te MIA-COV19 compe
Modifications of the official PyTorch implementation of StyleGAN3. Let's easily generate images and videos with StyleGAN2/2-ADA/3!
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net
HarDNeXt: Official HarDNeXt repository
HarDNeXt-Pytorch HarDNeXt: A Stage Receptive Field and Connectivity Aware Convolution Neural Network HarDNeXt-MSEG for Medical Image Segmentation in 0
ReSSL: Relational Self-Supervised Learning with Weak Augmentation
ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model
[ICCV 2021 Oral] PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers Created by Xumin Yu*, Yongming Rao*, Ziyi Wang, Zuyan Liu, Jiwen Lu, Jie Zhou
[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation
This is the official implementation of our paper: Bowen Wen, Wenzhao Lian, Kostas Bekris, and Stefan Schaal. "CaTGrasp: Learning Category-Level Task-R
[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation
[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation
This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild with Dense 3D Representations and A Benchmark. (CVPR 2022)"
Gait3D-Benchmark This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild
Code for the paper "Reinforced Active Learning for Image Segmentation"
Reinforced Active Learning for Image Segmentation (RALIS) Code for the paper Reinforced Active Learning for Image Segmentation Dependencies python 3.6
Cobalt Strike teamserver detection.
Cobalt-Strike-det Cobalt Strike teamserver detection. usage: cobaltstrike_verify.py [-l TARGETS] [-t THREADS] optional arguments: -h, --help show this
WatermarkRemoval-WDNet-WACV2021
WatermarkRemoval-WDNet-WACV2021 Thank you for your attention. Citation Please cite the related works in your publications if it helps your research: @
Awesome-google-colab - Google Colaboratory Notebooks and Repositories
Unofficial Google Colaboratory Notebook and Repository Gallery Please contact me to take over and revamp this repo (it gets around 30k views and 200k
The codes and related files to reproduce the results for Image Similarity Challenge Track 2.
ISC-Track2-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 2. Required dependencies To begin with
Reinforcement learning library in JAX.
Reinforcement learning library in JAX.
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I