*** Liveness for Mobile!! -- 2

$750-1500 USD

Imefungwa

Imechapishwa

over 3 years ago

$750-1500 USD

Kulipwa wakati wa kufikishwa

***Applying via email, skyppppe, linkedin, phone calls or post pigeons will get you disqualified immediately!. Only apply to this job here! We are looking for a liveness / anti-spoofing feature to prevent still images AND video attacks for login, to be implemented in our Android App and iOS. ***Please explain what approach will you take in developing the liveness. ***Please start your msg with the words: "I have a liveness for Android!"

Machine Learning (ML)

Face Recognition

Kitambulisho cha mradi: 27938808

Kuhusu mradi

4 mapendekezo

Mradi wa mbali

Inatumika 3 yrs ago

Unatafuta kupata pesa?

Barua pepe

Faida za kutoa zabuni kwenye Freelancer

Weka bajeti yako na muda uliopangwa

Pata malipo kwa kazi yako

Eleza pendekezo lako

Ni bure kujiandikisha na kutoa zabuni kwa kazi

4 wafanyakazi huru wana zabuni kwa wastani $970 USD kwa kazi hii

@helmot

Hello, I have a masters degree in AI and have worked on AI/ML projects for 8+ years. If you are interested I can share my desktop and show you some demos/samples. I have worked with most AI/ML tools like NLTK and NLP modules in Python, Tensorflow, Image Processing tools/libraries, Hadoop, H2O, Also, I work as a fulltime freelancer and do not have any other job and can assign enough time to your project. Please feel free to leave me a message if you have any questions. Thanks, Helmot

$1,250 USD ndani ya siku 20

4.8

(1 hakiki)

3.9

@datacode0023

Hi, I have +5 experience dealing with machine learning algorithms and worked on multiple projects in this field, I absolutely can do your project as you like. Please contact me to discuss more. Have a nice day

$1,125 USD ndani ya siku 7

5.0

(1 hakiki)

1.6

@ppoojapatil844

"I have a liveness for Android!" Anti-spoof detection is a binary classification problem and can be solved using: 1. ML by extracting features from the images/frames (such as binary-coded features like LBP, difference measures, gradient measures, color-based statistical measures, etc.) and feeding these attributes to the classifiers like SVM to discriminate between live and spoof images, 2. DL with Neural nets like CNN to extract features and for classification. I have research experience in this topic and can work using any of the methods mentioned above as per the requirement. Looking to hear from you to start the work ASAP

$756 USD ndani ya siku 7