Posted on 05.04.2011 - 12:00 UTC in GENERAL NEWS by Rons_ROV_Links
SeeByte, the global leader in creating smart software technology for unmanned systems, is pleased to announce their most recent sale of SeeTrack Military to Defence Research and Development Canada (DRDC), the Canadian Forces' science and technology agency.
DRDC purchased the SeeTrack Military licence together with SeeByte's Performance Analysis & Training Tool (PATT) to help develop Automatic Target Recognition (ATR) algorithms for the Canadian Navy. Improved ATR will assist in one of the key challenges facing naval Mine Counter Measures (MCM): the ability to detect and classify objects, generating fewer false alarms and improving the value of data gathered. SeeTrack Military will provide DRDC with a tool for tactical system mission planning, asset tracking, data analysis and object correlation. PATT provides a platform on which they can analyse the performance of their ATR algorithms.
Ioseba Tena, Sales Manager at SeeByte said: "We are pleased to be working with DRDC to provide them with the capabilities and tools they require for their development of novel, state-of-the-art ATR solutions. SeeTrack Military is now the MCM planning and processing tool of choice for many navies. Our focus has been to deliver an operational tool suited to the needs of the war-fighter. However we have also worked hard to ensure that the navies are able to integrate their own and third party software capabilities to our own solutions. Our PATT module was designed to allow users to assess the MCM capabilities of a complete system, and we are confident it will benefit DRDC to trial, test and approve their ATR technology."
Vincent Myers of DRDC commented: "Our motivation in developing these ATR algorithms is to reduce workload for operators performing route survey and change detection, in turn creating more accurate and timely MCM information. By using SeeByte's SeeTrack Military software with the PATT module, we will be able to easily integrate our ATR algorithms into a recognised commercial product and assess potential improvements in the change detection process, which is currently considered to be highly operator intensive."