Microsoft improved the object detection capabilities of its ML.NET machine learning framework for .NET developers, adding the ability to train custom models with Model Builder in Visual Studio.

Microsoft in May announced Object Detection in ML.NET Model Builder. These capabilities are built on top of TorchSharp-powered Object Detection APIs introduced in ML.NET 3.0.

General availability of ML.NET packages to use TensorFlow and ONNX models: "ML.NET has been designed as an extensible platform so that you can consume other popular ML models such as TensorFlow and ...

FOMO is a deep learning object detection model that weighs less than 200 kilobytes.

This award is focused on delivering commercial analytic services, specifically automated AI/ML-generated object detections over many specified locations at once.