C-CORE has over 20 years of experience in leveraging satellite-based assets including Optical, SAR, RF, Multispectral, and AIS to extract insights such as dark target detection. C-CORE provides end-to-end services to rapidly task, interpret and share dark target information playing a critical role in broad maritime surveillance.
C-CORE is satellite sensor agnostic and uses over 60 satellites and growing satellites to detect and identify Maritime targets. C-CORE can forecast upcoming satellite passes for rapid tasking to increase the near real-time maritime surveillance.
C-CORE is a world leader in EO algorithm development specializing in target detection, classification, and identification leveraging AI to continuously improve the speed and accuracy of detection and classification predictions.
C-CORE leverages its easy-to-use Coresight solution delivery platform to provide dissemination of products/analytics via a web-based interface, notification services, as well as secure API access. Allowing end users to quickly visualize surveillance data and increasing the speed of decision making.
C-CORE’s MSS Service is directly intended to support the monitoring of EEZ, illegal fishing, illegal goods transfer, human trafficking, oil spill, as well as search and rescue scenarios.
Users can dynamically define AOI for C-CORE to actively monitor to detect dark targets. C-CORE predicts ship locations and can forecast and rapidly task high-resolution satellites to get a more detailed look before deploying expensive sea/aerial based assets.
In order to rapidly respond (sub-hour), C-CORE offers an early view of detection data alongside current AIS data prior to the delivery of the fully QA’d dark target detection product, to provide near real-time maritime awareness insights.
C-CORE has extended world-leading target detection/classification system used by the international ice patrol to globally monitor icebergs, ice concentrations, vessels, and offshore platforms to include high-confidence dark targets expanding an already robust maritime domain awareness.
C-CORE has extensive experience developing Machine learning algorithms to extract insight from Earth Observation data such as change detection, object detection (oil spills), and object classification (land, ship/icebergs, and ice classifications). C-CORE in partnership with Equinor ran one of the largest image classification contest on the internet using the Google owned Kaggle platform. The machine learning competition generated over 40,000 entries from over 3000 of the world's best data scientists. The success of this project was based on well curated/labeled data and underlying research to provide new EO data scientists a running start.