MetaTagger is an accredited GOTS ML test and evaluation toolset designed to streamline ground-truth data labelling and performance testing of imagery and Full Motion Video (FMV) based models. MetaTagger accelerates model testing to increase performance transparency, user trust, and model adoption. A smart collection of tools enable fast image labeling for training data purposes. Our custom-built tool called AutoTagger uses a Single Object Tracking (SOT) algorithm to automate object detection, labeling, and creation of ground truth datasets in less than half the time of manual approaches. Once Ground truth is created, FVM inference can be evaluated in minutes by simply uploading inference to the application and letting the MetaTagger algorithm work in the background. Once evaluation is completed, a filterable reporting tool allows custom reports to be generated and exported for future analysis. MetaTagger is the one-stop-shop for testing and evaluation of object detection and object classification algorithms.

MetaTagger - Computer Vision Testing & Evaluation Toolset

This is the second of four poster sessions

**Date & Time:**  Wednesday March 24th,  12-1:30pm PDT

**Location:** Poster Session Room 1B

The live poster sessions will happen in our Gather.Town lounge at the designated time. Each session has their own room. Once you click the gathertown button below, you will need to navigate to the Poster Session Room for each session located on the right side of the lounge. Each speaker will be by their poster where you can communicate with them and view their poster by clicking X on your keyboard.

[![](https://assets.underline.io/uploads/markdown_image/1/image/737a34c989ecf3ae95182670d99c072c.png)](https://gather.town/app/5IAViMZXC9ZF4E4l/NAML)

Poster Session 1B

poster

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

**Watch this video to hear about the AFCEA purpose.**

<iframe width=1280 height=706 frameborder="0" scrolling="no" src="https://screencast-o-matic.com/player/creleVVcvRh?v=6&ff=1&title=0&controls=1" allowfullscreen="true"></iframe>

Justin Nicholson

1

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MetaTagger - Computer Vision Testing & Evaluation Toolset

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