Archeron

May 11, 2020

SAR for Ship Detection

Ship detection with satellite imagery in the commercial space is primarily focused towards resolving issues pertaining to the environment, commerce, and national security. Due to the possibility of the presence of thick cloud cover over oceanic landscapes and the requirement of day-night monitoring of marine traffic synthetic aperture radar (SAR) systems have been adopted for the purpose of surveillance. Performance of such systems has been commendable over the past decades with high-resolution wide-swath systems orbiting the Earth providing high spatial & temporal coverage. The problem of detecting ships is looked at either from a target/object detection perspective or by observing anomalies over the undulating waters, like smooth morphological trails resembling the wake of the ship. Over several decades, ship detection with SAR was constrained by the availability of single-channel datasets that provided limited partial insights into the polarimetric scattering behaviour of the target.
May 11, 2020

Agricultural Applications with SAR

Across the globe, approximately one in every seven people go hungry every day. About 1/3rd of the agricultural produce is lost or wasted each year. As per the presently rising food demand agricultural yield needs to increase by 60% over the next 40 years to meet the projected demand. Agricultural land occupies approximately 38% of the available ice-free terrestrial land surface, which includes about 12% of croplands and 26% of pastures. Off the total available agricultural production human consumption amounts to 62% of the produce followed by animal feed amounting to 35% and a mere 3% for bioenergy and other industrial production. Unfavourable growing conditions can change the productivity of an agricultural field within a short span. Therefore, timeliness is the key to monitor such an adverse change that can impact the yield.
May 11, 2020

SAR Data Fusion With Other Sensors Like Optical & Hyperspectral

Remote Earth observation platforms capture data in different segments of the electromagnetic (EM) spectrum. An image is essentially a measure of interaction between the target material and the imaging wavelength. Such interactions are not discrete but rather continuous in nature and its magnitude varies as a function of varying wavelength. Therefore, information captured by a sensor tuned to a particular wavelength depicts only a discrete slice of response and is therefore not the comprehensive characterization of the target material. The fusion of multi-sensor datasets is thus an attempt to partially recreate and approach the continuous response curve of the target, which defines its absolute electromagnetic attribute.
May 10, 2020

Autonomous Artificially Intelligent Robots in Banking and Retail

This paper explores the applications which robotics can assume in the field of finance and retail. The paper talks about a Robotic Framework with both hardware and algorithmic details.