You will get š Professional Face Anti-Spoofing AI System - ā iBeta Level 2 Ready
Project details
Professional Face Anti-Spoofing System for banking and enterprise applications.
šÆ iBETA LEVEL 2 READY šÆ
š Images processed: 67k+
ā Accuracy: 99.6%
ā AUC: 0.99
ā EER: 0.009
ā ACER: 0.016
ā APCER: 0.00006 (1 in 67k)
ā BPCER: 0.03
What sets this apart:
ā¢ Near-perfect attack prevention (0.0063% APCER vs industry 1-5%)
ā¢ 250+ hours professional R&D investment
ā¢ Real-time processing <100ms response time
ā¢ Complete ownership, no per-transaction fees
ā¢ Multiple deployment options: mobile, API, Docker
ā¢ Banking-grade compliance ready
Perfect for: Banking KYC, fintech authentication, enterprise security, fraud prevention.
Includes: Production-ready model, Python, detection pipeline, comprehensive documentation, deployment guides, validation results.
4 Packages available from immediate delivery ($2,997) to exclusive licensing ($49,997).
Deploy enterprise-grade security at 50-60% below worldwide development rates.
š”ļø SECURITY COMPARISON
Solution APCER / Compliance Banking Ready
AWS Rekognition ~2-5% Basic ā No Per-call
Microsoft Face API ~3-7% Basic ā No Per-call
Google Vision API ~4-8% Basic ā No Per-call
š THIS SOLUTION < 1 % iBeta L2 ā Yes One-time
šÆ iBETA LEVEL 2 READY šÆ
š Images processed: 67k+
ā Accuracy: 99.6%
ā AUC: 0.99
ā EER: 0.009
ā ACER: 0.016
ā APCER: 0.00006 (1 in 67k)
ā BPCER: 0.03
What sets this apart:
ā¢ Near-perfect attack prevention (0.0063% APCER vs industry 1-5%)
ā¢ 250+ hours professional R&D investment
ā¢ Real-time processing <100ms response time
ā¢ Complete ownership, no per-transaction fees
ā¢ Multiple deployment options: mobile, API, Docker
ā¢ Banking-grade compliance ready
Perfect for: Banking KYC, fintech authentication, enterprise security, fraud prevention.
Includes: Production-ready model, Python, detection pipeline, comprehensive documentation, deployment guides, validation results.
4 Packages available from immediate delivery ($2,997) to exclusive licensing ($49,997).
Deploy enterprise-grade security at 50-60% below worldwide development rates.
š”ļø SECURITY COMPARISON
Solution APCER / Compliance Banking Ready
AWS Rekognition ~2-5% Basic ā No Per-call
Microsoft Face API ~3-7% Basic ā No Per-call
Google Vision API ~4-8% Basic ā No Per-call
š THIS SOLUTION < 1 % iBeta L2 ā Yes One-time
Machine Learning Tools
Caffe, Keras, Kubeflow, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, TensorFlowWhat's included
| Service Tiers |
Starter
$2,997
|
Standard
$7,997
|
Advanced
$29,997
|
|---|---|---|---|
| Delivery Time | 1 day | 40 days | 70 days |
Number of Revisions | 0 | 0 | 0 |
Number of Model Variations | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | ||
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
š iBeta Level 2 Certification Service
+$2,497
š Custom Dataset Integration
+$1,497
š¢ Enterprise Integration Service
+$1,997Frequently asked questions
34 reviews
(33)
(1)
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This project doesn't have any reviews.
ZH
Zachary H.
Feb 23, 2026
AI & ML Pipeline Documentation & Tutorial Creation
Frederico has now completed four contracts with us, and he continues to deliver at an exceptionally high level.
This project involved documenting and productionizing a complex machine learning workflow for multi-environment deployment. The scope included end-to-end documentation, automation scripts, containerized GPU builds, architecture diagrams, quick-start guides, and CLI execution examples.
Fred went far beyond basic documentation. He deeply understood the system, restructured the repository for clarity, eliminated duplication, and created a clean, professional, production-ready package.
He built reproducible Docker environments with GPU support, handled CUDA and PyTorch dependency alignment, performed fresh-install validation testing, and locked versions to ensure consistent results across machines. When we encountered packaging issues with an early container build, he quickly diagnosed the root cause and rebuilt the environment properly using a clean Dockerfile-based approach.
What stands out most is his mindset. He thinks like an infrastructure engineer, not just a contractor. He anticipates edge cases, cares about reproducibility, and focuses on long-term maintainability.
Communication is clear and proactive. He provides thoughtful tradeoff analysis when discussing upgrades (for example, dependency migrations), and he always validates before shipping.
If you need someone who can handle:
Complex ML workflows
GPU-enabled Docker environments
Dependency management across evolving toolchains
Clean technical documentation
Deployment-ready packaging
Frederico is an excellent choice.
We will absolutely continue working with him.
This project involved documenting and productionizing a complex machine learning workflow for multi-environment deployment. The scope included end-to-end documentation, automation scripts, containerized GPU builds, architecture diagrams, quick-start guides, and CLI execution examples.
Fred went far beyond basic documentation. He deeply understood the system, restructured the repository for clarity, eliminated duplication, and created a clean, professional, production-ready package.
He built reproducible Docker environments with GPU support, handled CUDA and PyTorch dependency alignment, performed fresh-install validation testing, and locked versions to ensure consistent results across machines. When we encountered packaging issues with an early container build, he quickly diagnosed the root cause and rebuilt the environment properly using a clean Dockerfile-based approach.
What stands out most is his mindset. He thinks like an infrastructure engineer, not just a contractor. He anticipates edge cases, cares about reproducibility, and focuses on long-term maintainability.
Communication is clear and proactive. He provides thoughtful tradeoff analysis when discussing upgrades (for example, dependency migrations), and he always validates before shipping.
If you need someone who can handle:
Complex ML workflows
GPU-enabled Docker environments
Dependency management across evolving toolchains
Clean technical documentation
Deployment-ready packaging
Frederico is an excellent choice.
We will absolutely continue working with him.
ZH
Zachary H.
Nov 14, 2025
Computer Vision Model Training & Evaluation for Synthetic Tank Dataset
Fred was instrumental in building and delivering a complex AI system from the ground up. He combines deep technical skill with rare persistence and creativity, solving problems that would have stopped most engineers. His communication, documentation, and ownership were world-class, and every deliverable exceeded expectations. Iād work with him again in a heartbeat for any advanced ML or computer-vision project.
ZH
Zachary H.
Sep 9, 2025
High-Quality Synthetic Image Generation with Annotation using Unity Gaming Engine (Assets Provided)
Frederico took our project's phase II from plan to production-ready. He refined 2,000+ images with consistent LoRA-based weathering, built a ComfyUI automated pipeline (batch + random prompt generator), delivered a custom Flux LoRA model, and integrated a YOLOv8 ā JSON annotation pipeline with QC visualizations. He documented everything, set up backups/version control, and proactively mitigated risks. Clear communication, fast iteration, and a strong product mindset. If you need Stable Diffusion / LoRA / ControlNet / ComfyUI and CV-ready datasets, hire him.
ZH
Zachary H.
Jul 9, 2025
High-Quality Synthetic Image Generation with Annotation using Unity Gaming Engine (Assets Provided)
Frederico is a world-class engineer who delivers incredible products. He excels at suggesting modifications to workflows within a project that result in better outcomes. He is extremely articulate when discussing technical tradeoffs around key decisions and is always happy to explain his thinking. I found him to be extremely trustworthy, high agency, and very efficient with his time.
JD
Johan D.
Nov 13, 2024
Graphics Optimization Expert for Microsoft Flight Simulator
About Frederico
Computer Vision | Spatial AI: Interactive Installations | 20+ years
86%
Job Success
Praia Grande, BrazilĀ - 9:56 am local time
š For 20+ years I've built production CV systems, real-time interactive installations, and generative AI experiences that run 24/7 in airports, malls and live global events, handling dozens of users simultaneously, in chaotic real-world conditions, where a crash is never an option.
š„ Bridging domains most engineers can't:
- Computer Vision + Generative AI + Real-Time Interactivity. Most engineers know Computer Vision. Others know Generative AI. Few have shipped both together in the same production interactive system, under live-event conditions, for global Fortune 500 brands. That's the gap I live in.
šÆ Spatial AI is the fusion of real-world interactivity with Generative AI and intelligent agents. In practice, it means I can build:
- An interactive wall that tracks users and generates unique, on-brand visuals in real time, pipelines serving dynamic assets directly into Unity / Unreal at scale.
- A context-aware AI character that sees you, hears you, remembers your interactions, and responds with personality, powered by RAG, MCP, and multimodal sensing.
Need a ComfyUI pipeline feeding Unity visuals live? A multi-sensor agent that understands physical space? A face recognition system that works in any crowd, any lighting? That's where I thrive.
ā ā ā ā ā CORE EXPERTISEā ā ā ā ā
ā Interactive Installations & Gamified Experiences
- Unity / Unreal Engine Ā· Interactive walls (DLSS 4K+, 50+ users) Ā· Projection mapping
- Character-driven gamification Ā· Custom hardware (Jetson, Arduino, ESP32)
ā Depth Camera & Spatial Vision
- Kinect v1/v2/Azure Ā· RealSense Ā· Orbbec Ā· Multi-camera sync
- 3D reconstruction Ā· Sensor fusion (LiDAR + depth + RGB + IMU)
ā Computer Vision & Deep Learning
- Face recognition & anti-spoofing (iBeta Level 2 ready)
- Real-time object & gesture tracking (MediaPipe, YOLO)
- Custom PyTorch / TensorFlow training on GPU
ā Generative AI & Synthetic Data
- Stable Diffusion XL Ā· Flux Ā· ComfyUI Ā· LoRA Ā· ControlNet Ā· Kohya
- Automated synthetic dataset generation, Dockerized pipelines
ā AI Agents & Spatial Intelligence
- RAG systems Ā· MCP integration Ā· Memory-enabled context-aware agents
- Edge-deployed LLMs Ā· Sub-100ms multimodal inference
š NOTABLE ACHIEVEMENTS
- Face Anti-Spoofing AI (2025): 99.6% accuracy, 1 in 67k false accepts, <100ms, iBeta Level 2 ready
- Synthetic Dataset Pipeline (2025): 27K images, 99.2% F1, fully Dockerized
- Formula 1 SGP: Live 3D projection mapping on a real F1 car, 4 projectors + 3 Kinects, zero failures
- LancƓme AR: +20% audience engagement, real-time facial tracking at 120fps
- Manulife LED Wall: 5 Kinects synced across PCs, 30+ concurrent users, 24/7 reliability
- Hugo Boss, Changi Airport T1: Live multiplayer Kinect installation, high foot traffic
- Adidas Interactive Wall: Motion-reactive 8K wall with Unity DLSS shaders
- Cirque du Soleil AR: Real-time AR masks with instant Polaroid print and email share
š„ TESTIMONIALS
āāāāā "Fred is the best freelancer I've worked with, extremely competent and passionate. We've worked together for over 6 years!"- Joel Goh, Creative Director, Trinax Sg
āāāāā"World-class engineer who delivers incredible products. Excels at suggesting modifications that result in better outcomes."- Zach
āāāāā "Outstanding work. Great communication. Very pleased with creative input and visual aesthetics on our VR app. Will hire again."- Michael Jenkins, Harmony Media
āāāāā"Fred's technical expertise is unmatched. His research-driven approach led to an outstanding result. Highly recommended!"- Iman Shirali, Elitaz
š ļø TECH STACK
- Languages: Python Ā· C++ Ā· C# Ā· JavaScript Ā· HLSL
- CV / ML: PyTorch Ā· TensorFlow Ā· OpenCV Ā· MediaPipe Ā· YOLO Ā· SAM
- Generative AI: LoRA - ControlNet Ā· ComfyUI - Kohya - Stable Diffusion Ā· Flux
- LLM & Agents: Multi-Agent Orchestration Ā· Parallel Workers Ā· Persistent Memory - MCP - RAG
- Depth & 3D: Lidar - Kinect Ā· RealSense Ā· Orbbec Ā· PCL
- Engines: Unity (XR Toolkit, Shader) Ā· Unreal Engine Ā· Blender Ā· Houdini
- Vector DBs: ChromaDB Ā· Pinecone Ā· FAISS
- Infrastructure: AWS Ā· Azure Ā· Firebase Ā· Supabase Ā· Docker Ā· MLflow Ā· W&B
šÆ IDEAL PROJECTS
ā Production-grade interactive installations, walls, projection mapping, gamification
ā Computer vision that works in real crowds, any lighting, any hardware
ā Spatial AI with memory and personality, retail, museums, brand experiences
ā Generative AI pipelines for dynamic, personalized real-time content
ā Biometric systems, face recognition, anti-spoofing, liveness detection
ā Multi-sensor edge deployments, events, airports, malls, retail
š« LET'S TALK
I specialize in solving problems others say can't be done.
Send me your technical challenge, timeline, budget, and success metrics.
I'll respond within 24 hours with a clear plan and cost breakdown. Because I think like a founder, not just a developer.
Steps for completing your project
After purchasing the project, send requirements so Frederico can start the project.
Delivery time starts when Frederico receives requirements from you.
Frederico works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Requirements Analysis & Package Selection (Day 1)
ā Review your requirements form ā 30-minute consultation call (free) ā Recommend optimal package tier ā Provide custom timeline & pricing ā Sign agreement & begin work
Step 2: Immediate Core Delivery (Day 1-2)
ā Deliver production-ready AI model (99%+ accuracy) ā Provide complete validation results (67K+ images tested) ā Include demo application & integration guide ā Setup instructions & technical documentation ā Verify successful deployment on your system