Abstract: A system and method for object monitoring, detection, and segmentation in electro-optical (EO) satellite imagery data comprising an image processing engine configured to prepare EO data for analysis by an inference engine which utilizes one or more trained models to perform object detection or image segmentation. The workflow begins with ingesting satellite data, followed by de-hazing to remove atmospheric interference. Image enhancement improves resolution and geo-registration ensures precise spatial alignment. The processed image is then fed into a machine learning-based object detection or image segmentation network, trained to identify specific objects of interest. This integrated approach leverages advanced technologies to extract actionable insights from satellite data, enabling efficient and precise object monitoring, detection, and segmentation.

Abstract: Technologies for self-regulation for virtualized environments may include, by a virtual machine on an electronic device, detecting an attempted anti-malware operation by a monitored module, determining anti-malware operation levels of one or more other virtual machines on the electronic device, and, based on the attempted anti-malware operation and upon the anti-malware operation levels, determining whether to allow the attempted operation.

Abstract: Technologies for self-regulation for virtualized environments may include, by a virtual machine on an electronic device, detecting an attempted anti-malware operation by a monitored module, determining anti-malware operation levels of one or more other virtual machines on the electronic device, and, based on the attempted anti-malware operation and upon the anti-malware operation levels, determining whether to allow the attempted operation.