Better Quantifying the Performance of Object Detection in Video
One of our research scientists, Cameron Wolfe, examines how the industry evaluates the quality of video-based annotations for computer vision applications.
Single Object Tracking Using The Siamese Family of Trackers
Object Tracking is an inherently challenging computer vision task. In this piece, we explore how Siamese Neural Networks are powering recent developments.
Data Labeling for Enterprise AI & ML Experimentation
This whitepaper shows how more experiments & smaller volumes of data help high-performing AI teams build baselines quickly & rapidly iterate to improve.
This white paper identifies the applications most suitable to supervised verses unsupervised approaches and delineates how to create a sound data strategy.
Alegion's Data Science Team put together a whitepaper on annotation guidelines and improving the quality of labeling data. Download a complimentary copy.
Three key aspects to consider when choosing a video annotation platform for computer vision: Entity Persistence, Detecting State Change, Temporal Tagging.
AI & ML projects are still nascent according to Dimensional Research's survey of 277 data scientists and other AI professionals across nearly 20 industries
