AI Computer Vision

Deep Learning Algorithms in Computer Vision.

AI Computer Vision is a branch of artificial intelligence that allows computers to extract meaningful information from digital images, videos, and other visual inputs, enabling them to make decisions or recommendations. We leverage our expertise and passion to create custom AI solutions for your complex image processing and analysis needs.

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Embedded AI Solutions

Specialized in resource-constrained environments — we bring production-grade computer vision to IoT devices, mobile platforms, and edge hardware where cloud connectivity is unavailable or undesirable.

  • Minimal memory footprint — optimized models under 1 MB
  • Real-time inference on MCUs, NPUs and mobile SoCs
  • No cloud dependency — fully on-device processing
  • Scalable and adaptable across hardware generations
Mobile IoT / MCU NPU / Edge Embedded Linux
Training Data Images · Labels · Augmentation
Model Training Architecture · Optimization · Validation
Edge Optimization Quantization · Pruning · TensorRT / ONNX
Key step
Mobile
IoT / MCU
Edge Server

Build. Optimize. Deploy.

A proven 6-step process from requirements to continuous improvement — delivering robust, production-ready AI systems.

01

Understanding Your Needs

Thorough analysis of requirements, objectives, and constraints. Business needs assessment, technical feasibility evaluation, and scope definition.

Requirements Feasibility Scope
02

Data Collection & Preprocessing

Gathering diverse image datasets, cleaning, preprocessing (resizing, normalizing, augmenting), and proper labeling and annotation.

Datasets Augmentation Annotation
03

Feature Extraction

Using SIFT, HOG, and CNN (Convolutional Neural Networks) for hierarchical feature learning from visual data.

SIFT HOG CNN
04

Model Training

Architecture selection, model training on curated datasets, hyperparameter optimization for robust, scalable results.

Architecture Optimization Validation
05

Deployment

Multi-platform deployment (cloud, edge devices), processing pipeline optimization, and real-time performance assurance.

Cloud Edge Real-time
06

Testing & Monitoring

Extensive testing under diverse conditions, user feedback incorporation, continuous refinement, and model improvement based on new data.

Testing Feedback Improvement

Technologies & Capabilities

A complete stack of computer vision techniques — from classical algorithms to state-of-the-art deep learning models.

Object Detection

Real-time detection and classification of multiple objects in images and video streams using YOLO, SSD and transformer-based architectures.

YOLOSSDDETR

Image Segmentation

Pixel-level understanding of scenes with semantic and instance segmentation for precise object delineation and scene parsing.

SemanticInstancePanoptic

Optical Character Recognition

Accurate text detection and recognition in complex scenes, documents, and constrained environments for data extraction pipelines.

Scene TextDocumentsMultilingual

Pose Estimation

Human body, hand and facial landmark detection for gesture recognition, activity analysis and ergonomic monitoring applications.

Body PoseHand TrackingFace Landmarks

Anomaly Detection

Unsupervised detection of visual defects, outliers and abnormal patterns in manufacturing, security and medical imaging.

UnsupervisedDefect DetectionQuality

Depth Estimation

Monocular and stereo depth estimation for 3D scene reconstruction, obstacle avoidance and spatial awareness on embedded platforms.

MonocularStereo3D Reconstruction

Proven Results

Our face recognition technology — a direct application of our computer vision expertise — is independently evaluated by NIST and deployed at scale worldwide.

0.002
False Non-Match Rate

At FMR = 0.000001 on NIST FRTE Mugshot-Mugshot — among the best accuracy/speed tradeoffs evaluated.

NIST FRTE 1:1 — id3_009
9 ms
Face Recognition on Mobile

Full detection + extraction pipeline on iPhone 12 — real-time performance without compromise on accuracy.

Tested on iPhone 12
45 ms
1M-face Identification

One-to-many search across 1 million face templates in under 50 ms — enabling large-scale ABIS deployments.

NVIDIA GTX 1080 Ti
148 B
Template Size

Face template under 148 bytes — among the smallest on the market, enabling deployment on the most constrained hardware.

MicroFace SDK

Why id3 Technologies

25+ years of biometric and computer vision R&D — delivering production-grade AI where others stop at prototypes.

25+
Years of R&D

Deep expertise in computer vision, biometrics and embedded AI since 1998 — solving real-world problems, not just benchmarks.

NIST
Certified Algorithms

Our algorithms are independently evaluated and ranked by NIST — a guarantee of accuracy and reliability at scale.

Full
Stack Ownership

From dataset curation to deployment and monitoring — we own the entire pipeline and deliver complete, maintainable solutions.

Application Domains

From security to healthcare, our computer vision solutions are deployed across demanding real-world environments.

Security & Surveillance

Intrusion detection, object tracking, and real-time video stream analysis for enhanced security monitoring.

  • Intrusion detection
  • Object tracking
  • Real-time video analysis

Automotive

Driving assistance systems, pedestrian detection, and traffic sign recognition for safer transportation.

  • Pedestrian detection
  • Traffic sign recognition
  • Driver assistance

Healthcare

Medical image analysis, early disease detection, and tumor growth monitoring for improved diagnostics.

  • Medical image analysis
  • Early disease detection
  • Tumor monitoring

Industry

Quality control processes, process automation, and predictive maintenance for manufacturing efficiency.

  • Quality control
  • Process automation
  • Predictive maintenance

Get started with our technologies.

Contact us to learn more about our biometric and security solutions and discover how it can transform your products and services. With id3 Technologies, step into a world where technology meets security, innovation, and reliability.

Contact us