caoloss's repositories
newconvert
Landmark University - Hospitality Unit, New Convert Web App. Technologies used: Adonisjs, Vuejs and MySQL
px-dev
PX-Developer is scale-out storage for containers. Run Cassandra, Jenkins, or any application in Docker, with enterprise storage functionality on commodity servers
World-Happiness-Report-2019-Machine-Learning-Prediction-
World Happiness Report is a landmark survey of the state of global happiness that ranks 156 countries by how happy their citizens perceive themselves to be. This year’s World Happiness Report focuses on happiness and the community: how happiness has evolved over the past dozen years, with a focus on the technologies, social norms, conflicts and government policies that have driven those changes.
PROI_proj1_zbiory
SETS OF THE POINTS IN A CARTESIAN LANDMARK - My very first project in C++ as part of the Object Programming Course at the 2nd semester of the Computer Science degree at Warsaw University of Technology
Hi-Tech-World-School
It is a website for the school which is landmark of hi-tech institute of engineering and technology, ghaziabad, It is a live project.
kubernetes-deployment
yml files for kubernetes-deployment for springboot application
Transfer-Learning-Face-Anti-Spoofing-Attack-Model
This repository contains the jupyter and mathematica notebooks of the Transfer Learning Model on VGG16, ResNet 50 architecture with ImageNet weights and FaceNet, and also our code proposed of the technique anti spoofing in the paper "Face Liveness Detection Based on Perceptual Image Quality Assessment Features with Multi-scale Analysis". Our project is about a Transfer Learning CNN on VGG16 architecture because it has the best results with an accuracy of 93,016 % in CASIA dataset, 97,321 % MDP dataset and 91,142 % NUAA dataset, we use a "real-time" landmark detection however the transfer learning model and landmark detection don't work together yet (our future work is that these two technologies can work together to reduce errors and improve the accuracy). This also contains the full paper of the "Anti Spoofing Face Detection Technique based on Transfer Learning Convolutional Neural Networks and Real-Time Facial Landmark Detection" to the Latinx in AI - ICML Workshop call.
aws-k8s-kops-ansible
Kubernetes setup on Amazon AWS using Kops and Ansible
CentOS7_Lockdown
Hardening CentOS7 - CIS
Face_Landmarks_Detection
A facial landmarks detection system is a technology capable of detecting a person from a digital image or a video frame from a video source. There are multiples methods in which facial detection systems work, but in general, they work by comparing selected facial features from given image with faces within a database.
hellokube
This is repository holds hello kubernetes example deployment yml files
HackathonSpring17_ParkingReservation
GO Parking is a online parking reservation web application developed on MEAN stack. It helps users to find the right parking area and reserve it. The application provides user registration form for user to sign into the application. User can take the benefit of Facebook or Google O Auth to validate himself/herself into the application. User can find the right parking location by entering the address/landmark/city. Using the information, the application makes a REST API service call to ParkWhiz api to fetch the parking details. The results are shown in two views for better user experience. The parking locations are shown on Google Maps as well as List View. User can then select any one parking location which shows the parking layout of the building. The user gets to choose from any available parking slots to proceed further to reserve the spot. The parking details like Location Name, Location Address, Price, From Time, To Time and vehicle registration number are taken to make a reservation. The details are then pushed into mongoDB and an email confirmation is trigerred from nodejs which is sent to registered emailid. The application also provides feature for the user to delete his reservation or user account. This can be accessed from 'My Account' page of the application. Technologies Used: 1. MEAN stack 2. Google Maps API 3. Bootstrap, jQuery 5. Amazon Web services
TUQuest
A game to explore the landmarks of the 'University of Technology' in Vienna.