Detection and classification
Identify defined objects, events or visual categories in images or video streams.
Computer Vision & ML
Turn images, video and data into useful operational signals.
SAWQ explores computer vision and machine learning for task-specific detection, classification, monitoring and prediction. We focus on whether the model improves an actual workflow, how it will be evaluated and what should happen when confidence is not high enough.
Applied vision and ML work
Start with the visual signal you actually need.
Model choice, data preparation, thresholds and review paths depend on what must be detected, how errors matter and what happens after a detection.
Vision-assisted monitoring
Convert relevant visual events into structured alerts, dashboards or downstream actions.
Machine learning integration
Integrate task-focused models into software products, APIs or operational workflows.
Evaluation and validation
Define appropriate data splits, metrics, thresholds and human review paths so performance is understood in context.
How we approach it
Define the event, evidence and acceptable error before training a model.
We start with the decision the system must support, then assess data availability, labels, deployment constraints and the cost of false positives or false negatives. A prototype is useful only when it can be evaluated against the real task.
Build with SAWQ
Have a visual task to evaluate?
Share the images or video context, the event you want to identify and what should happen when the system finds it.