Log in Subscribe

Tutu Rulianda

Tutu Rulianda

Hi I'm Tutu Rulianda. I worked as a programmer/analyst for Ernst & Young Consulting in Jakarta, Indonesia for seven years, and I have other software engineering professional experience under my belt.

South Tangerang, Indonesia https://kodemetrix.tuturulianda.com 19 posts

Photo by Max Chen / Unsplash

Scening Text Detection And Recognition Using RabbitMQ & Tesseract

Tesseract is an open-source OCR engine maintained by Google. It is capable of recognizing text within images, PDFs, and other scanned documents. RabbitMQ is a message broker that enables different parts of a system to communicate with each other by passing messages independently and asynchronously.

3 May 2024 · 3 min read

Photo by Possessed Photography / Unsplash

Implementing Openface In a Linux VPS Using Python and Docker

Openface provides capabilities for face detection, facial landmark detection, face recognition, and tracking facial expressions. OpenFace is an open source that's built using deep learning techniques and is capable of processing images and videos to analyze faces in real time or from recorded media.

3 May 2024 · 3 min read

Pixabay - Microphone

Speech Synthesis Implementation Using Vanilla JavaScript

Text-to-Speech (TTS) synthesis is the process of converting written text into spoken language. It involves analyzing the input text and generating corresponding speech output, often using algorithms and models to mimic human speech patterns and intonation. TTS systems use neural network techniques.

22 Apr 2024 · 3 min read

Pixabay - Human Brain

Back to Basic: Between Neural Network and Deep Neural Network

Neural networks (NNs) tend to be for simpler tasks, limited computing resources, or when interpretability is critical. Deep neural networks (DNNs) excel at performing complex tasks, leveraging large datasets, achieving state-of-the-art performance, and learning hierarchical representations of data.

20 Apr 2024 · 7 min read

Pixabay Artificial Intelligence

Back to Basic: Every Detail About Artificial Intelligence Subsets

AI has subsets as follows. ML for data-driven predictions, DL for complex pattern analysis, NLP for language understanding, CV for image processing, and RL for decision-making through rewards. Artificial intelligence revolutionizes industries, enhancing efficiency, innovation, and decision-making.

19 Apr 2024 · 16 min read

Unsplash.com - Aldi Sigun Shubham Dhage Javier Miranda Abhipsa Pal Milad Fakurian

Thin-Plate Spline Motion Model Usage for Image Animation

A static object in a source image transcends its immobility and awakens movement and energy through this transforming process of computer vision and pattern recognition, driven by the narrative pulse of a driving video. It requires an unsupervised motion transfer architecture to close the pose gap.

16 Apr 2024 · 2 min read

Pixabay - Face Biometrics

Back to Basic: What Is Face Biometrics and How Does It Work?

Facial recognition technology presents a complex blend of benefits and challenges. While it offers enhanced security and convenience, it also poses significant ethical and privacy issues. As the technology continues to evolve, it will be crucial to develop frameworks that ensure its responsible use.

13 Apr 2024 · 8 min read

Face Biometrics Stack

Face Biometrics Stack: Techniques, Applications, and Future Prospects

Face biometrics utilize facial recognition for security accurately and efficiently. Techniques include 3D mapping and AI algorithms. Applications range from unlocking phones to airport checks. Prospects involve enhancing accuracy and privacy, with potential growth in personalized user experiences.

11 Apr 2024 · 2 min read

Pexels - Cottonbro Studio

Enhancing Security with 3D Liveness Detection in Biometric Systems

Traditional 2D biometric systems are vulnerable to spoofing attacks, where adversaries can deceive the system using counterfeit images or videos. It's necessary to integrate 3D liveness detection technologies to address these vulnerabilities and enhance security and reliability in authentication.

27 Feb 2024 · 4 min read

Pexels - John Valette

Enhancing Security through 2D Liveness Detection in Biometric Systems

Biometric authentication systems can be compromised by using counterfeit biometric data. To combat this unauthorized access, the integration of 2D liveness detection techniques has emerged as an indispensable component, fortifying the security and dependability of biometric authentication systems.

23 Feb 2024 · 4 min read

Pixabay Mesh Networks

Reducing The Number of Mitigation Workflows to The Barest Minimum

Adopting proactive steps targeted at lowering susceptibility and exposure is one way to resolve security breaches, rather than depending exclusively on mitigation efforts. This is a complex plan that includes safeguards, strong security procedures, and a sturdy machine-learning infrastructure.

18 Feb 2024 · 3 min read

Photo by C M / Unsplash

KodeMetrix Online User Facial Profile Removal Implementation

KodeMetrix now provides free online facial profile removal for removing facial identification profiles from the face recognition database. Should you need to give it a try, please scroll down this screen to carry out the face profile removal procedure. Fill in the enrolled full name then tap Enter.

8 Feb 2024 · 3 min read

iStock by Getty Images - Credits Izusek

KodeMetrix User Face Registration Concept and Implementation

KodeMetrix now offers free face registration. Should you need to give it a try with the facial recognition registration process, head over to the app. Fill in your full name or any name, then tap the Button twice. If your face profile matches the one from the database then your entry will be denied.

3 Feb 2024 · 3 min read

Pixabay Camera

KodeMetrix Real-Time Face Biometrics Concept and Realization

KodeMetrix now provides a collection of facial recognition and detection implementations for desktop and mobile versions. Most of the web apps are based on FaceAPI-JS except the one that is based on Exadel CompreFace JavaScript SDK. These web apps need ample client processing power to process data.

1 Feb 2024 · 1 min read

Photo by ShareGrid / Unsplash

KodeMetrix Real-Time Multiple-Face Recognition Realization

A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces. KodeMetrix utilizes JavaScript SDK provided by Exadel CompreFace in the context of frontend web user interfaces both for desktop version and mobile version.

1 Feb 2024 · 3 min read

Photo by Robert Shunev / Unsplash

KodeMetrix Real-Time Face Expression Recognition Realization

Video streams are recorded by cameras, and algorithms are used to extract information such as wrinkle patterns, lip curvature, and eyebrow location. It classifies emotions such as happiness, sadness, rage, or surprise by feeding these elements into trained models on datasets of labeled expressions.

1 Feb 2024 · 2 min read

Photo by Toby Hall / Unsplash

KodeMetrix Real-Time Age and Gender Recognition Realization

Machine Learning can predict age and gender by analyzing various characteristics that are correlated with age and gender. The characteristics comprise analyzing biological features, behavioral patterns, text analysis, demographic information, feature engineering, and model selection and training.

1 Feb 2024 · 3 min read

Photo by Donald Giannatti / Unsplash

KodeMetrix Real-Time Face Landmarks Detection Realization

Machine learning can detect landmarks relying on a certain task and the nature of the landmarks being detected. Some common approaches are feature detection and matching, convolutional neural networks, facial landmark detections, geometric models, graph-based approaches, and point cloud processing.

1 Feb 2024 · 3 min read