The Target Separation Algorithms (TSAs) are used to improve the results of Automated Target Recognition (ATR). The task of the TSAs is to separate two or more closely spaced targets in Regions of Interest (ROIs), to separate targets from objects like trees, buildings, etc., in a ROI, or to separate targets from clutter and shadows. The outputs of the TSA separations are inputs to ATR, which identify the type of target based on a template database. TSA may include eight algorithms. These algorithms may use average signal magnitude, support vector machines, rotating lines, and topological grids for target separation in ROI. TSA algorithms can be applied together or separately in different combinations depending on case complexity, required accuracy, and time of computation.
Youtube
Update from Gary: Our #GivingTuesday match ju...
Duration:
1m 23s
Into Flight Once More Documentary Narrated Ga...
We are excited to announce that the feature-length documentary Into Fl...
Duration:
31s
Thank You to the Reddit Community
Our very own Gary Sinise wanted to thank the Reddit community for all ...
Duration:
15s
Airmen Helping Airmen Vodcast: Season 3, Epis...
In this episode of Airmen Helping Airmen, #AFAS CEO K. Wright sits dow...
Duration:
45m 11s
Gary Sinise Foundation Official Promo 2022
Get More GSF: Like GSF on FACEBOOK: Follow GSF on TWITTER:...
Duration:
1m 1s
My World Cup Predictions, Soccer in the US, a...
Today's episode of the GaryVee Audio Experience is an awesome conversa...