Computer Vision is a discipline within artificial intelligence that trains systems to interpret and understand information from digital images, videos, and other visual inputs. Our approach treats visual data as a rich source of information that can be systematically analyzed to automate tasks, identify anomalies, and generate critical operational insights.
Our Approach & Capabilities
We develop and deploy computer vision models that can "see" and interpret the world with a high degree of accuracy and consistency.
- Object Detection & Tracking: Identify, locate, and track specific objects of interest within an image or video stream for applications in security, retail analytics, and logistics.
- Image Classification & Recognition: Accurately classify images into predefined categories, enabling automated quality control, product identification, and content moderation.
- Image Segmentation: Partition an image into pixel-level segments to differentiate objects from their background, a critical step for medical imaging analysis and autonomous navigation.
- Optical Character Recognition (OCR): Extract printed or handwritten text from images and documents, enabling the digitization and automation of document workflows.
Business Impact
Our computer vision systems provide a scalable and tireless capability to monitor, analyze, and react to the visual world, leading to enhanced security, improved quality assurance in manufacturing, and new opportunities for customer engagement.
Technologies We Use
- Frameworks: OpenCV, YOLO, TensorFlow, PyTorch
- Platforms: Google Cloud Vision AI, Amazon Rekognition, Azure Cognitive Services for Vision