Detection and segmentation
Custom object detection, instance and semantic segmentation, training pipelines, model selection, and failure analysis.
COMPUTER VISION CONSULTING
Move computer vision from benchmark to real-world operation.
I help teams design data, models, video pipelines, evaluation, and deployment around the environments where the system must actually perform.
Tracking and video analytics
Multi-object tracking, event logic, camera streams, operational dashboards, and real-time video processing.
Datasets and annotation
Data collection strategy, annotation design, automated validation, versioning, privacy, and representative evaluation sets.
Edge and GPU deployment
NVIDIA DeepStream, TensorRT, OpenCV, model optimization, throughput benchmarking, and constrained-device inference.
PRODUCTION FIRST
Accuracy is not the only system metric.
A production vision system must handle camera failures, changing light, motion blur, unfamiliar environments, data drift, latency constraints, and the operational cost of false decisions.
The work starts with the decision the system needs to support. From there, we define data requirements, select or train an appropriate model, benchmark the complete pipeline, and build monitoring around the conditions most likely to fail.
The result is an engineered application with measurable behavior, not a model file handed over without the surrounding system.
COMMON ENGAGEMENTS
Computer vision systems built around the operation.
Industrial inspectionDefect detection, quality control, traceability, and human review.
Video intelligenceDetection, tracking, zones, events, counting, and live analytics.
3D and spatial visionDepth estimation, calibration, point clouds, visual odometry, and measurement.
Dataset infrastructurePrivate annotation, quality validation, versioning, and export workflows.