An embedding space is a high-dimensional mathematical space in which objects such as images, text, or sensor data are represented as vectors, enabling similarity search and pattern recognition in AI-powered infrastructure inspection systems.
TarmacView uses embedding space techniques to enable accurate automated detection and classification of pavement distresses from aerial and ground-level imagery.
Semantic segmentation assigns a category label to every pixel in an image, enabling full-scene understanding for infrastructure inspection. Covers encoder-decod...
AI-based crack detection uses computer vision — convolutional neural networks, vision transformers, and semantic segmentation models — to automatically identify...
FAISS (Facebook AI Similarity Search) is an open-source library for efficient similarity search and clustering of dense vectors, used by TarmacView to store and...
