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How It Works

The Robovision AI Platform was developed based on extensive experience in large-scale and unpredictable production environments. After more than a decade of implementing computer vision AI solutions across the world, two main success criteria emerged: computer vision AI implementations require reliable data and should be easy to maintain. 

The Robovision computer vision AI platform tackles these challenges—and is user-friendly, too.

1. Data Import

✓ Upload compressed folders automatically tagged with metadata

Customizable importer tailored to specific company workflows

✓ Metadata like Process ID or Device ID included for seamless integration

✓ Easily searchable & filterable

2. Data Annotation

✓ Advanced annotation tools, including single and multiview labeling

GrabCut and Magnetic Lasso for fast segmentation

✓ Filtering options based on user, date, or review status metadata

Predictive Annotator for AI-assisted labeling of new data (with user adjustments)

✓ Confusion matrix for annotation comparison

3. Data Curation

Tagging and filtering based on metadata to organize and inspect data, plus

Training data analytics ensure class balance with graphical class distribution analysis 

Auto training/validation set creation with stratified splitting for balanced class representation

Ground truth selection supports flexible strategies: selecting last updated annotations, annotations by specific users, manual selection, or random sampling

Immutable training datasets with fixed links to select ground truth annotations

4. Model Training

✓ Interactive progress monitor for real-time visualization of training metrics

✓ Supports hyperparameter tuning

✓ Configure to industry-standard parameters: early stopping, input resolution, batch size, learning rate, and more with Default or Expert mode

Transfer learning capabilities to other users to improve existing models by training with additional datasets.

✓ Assess multiple models based on performance, parameter settings, and the datasets used with detailed trained model comparison

 

 

5. Model Testing

Evaluate new model performance against the ground truth.

✓ Robust model performance evaluation

✓ Assess models against annotated test sets or specific user inputs

✓ Supports test comparison; select the best model by comparing same dataset performance with multiple models

Model self-check feature allows the model to test its validation data

✓ Identify outliers and potential label impurities for higher model accuracy and data quality

 

6. Model Optimization

Improve classification performance with optimized resource management.

✓ Powerful model optimization tools

✓ Can classify uncertain samples into an “unknown” class, protecting against model drift; triggers model maintenance when the “unknown” ratio becomes high

✓ Platform includes class confidence threshold optimization

✓ Set thresholds per class to identify valuable samples for re-labeling post-inference

Model confidence threshold optimization adjust overall confidence levels based on available manual classification capacity

 

7. Model Deployment

Model performance and reliability in a variety of production environments.

✓ For running inference: flexible deployment options, centrally or on fab floor

✓ Configure parameters and choose deployment options

✓ With Model Inference feature, send new samples and receive predictions via API endpoint

Model Monitor offers detailed reporting, tracking metrics like “unknown” rate and identifies low-confidence samples

 

 

 

 

simplicity simplicity

No-code interface

Our platform is designed for simplicity and versatility. With a no-code interface, operators without specialised AI skills can adapt and maintain AI models. This ensures your machinery remains state-of-the-art without requiring ongoing investments in specialised personnel. Robovision also supports a wide range of hardware and deployment options, whether cloud or on-premises, giving you flexibility in integrating AI into your existing infrastructure.

The no-code interface in action

Built-in Algorithms

Semantic Segmentation
Assign a class to every pixel in the image.
Instance Segmentation
Segment zones of interest on the frame with masks.
Classification
Classify what is seen into different categories.
Object Detection
Locate objects or people in the frame.
Anomaly Detection
Spot anomalies in the frame.
Multiview Classification
Classification using information from different views.

Strategic partner

Robovision is not just a technology provider; we're a strategic partner committed to extending the maximum value of your machine portfolio. We offer services to integrate and productize AI seamlessly, reducing risks and shortening the development timeline. By choosing Robovision, you're not just upgrading your machines—you're preparing your business for a future where smart, adaptable machinery is the norm.

LEARN MORE ABOUT PARTNERS
Success Stories
Client National Institutes of Health (USA)
Industry Healthcare
AI application makes it easier for radiologists to identify specific organs and detect anomalies.
View success story
Client ISO Horti Innovators
Industry Agriculture
See how the robot trims rose cuttings from a branch and pots them in one operation.
View success story
Client DEME Group
Industry Computer Vision AI Automation
Computer vision AI-based automated system that detects and identifies waste in a river.
View success story
Client ILVO
Industry Agriculture
AI-powered drones for weed detection enable hyper-localized spraying.
View success story