Radar Image Segmentation using Second-Order Recurrent Networks

• A second-order recurrent artificial neural network architecture for the segmentation and integration of radar images is introduced in this paper. This architecture consists of two sub-networks: a function network that classifies radar measurements into four different categories of objects in sea environments (water, oil spills, land and boats), and a context network that dynamically computes the function network's input weights. It is shown that this mechanism allows networks to learn to solve the task through a dynamic adaptation of their weighting of different radar measurements.behaviour.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

Nyckelord

classification

radar image segmentation

recurrent artificial neural networks

Computer and systems science

Data- och systemvetenskap

Publikations- och innehållstyp

vet (ämneskategori)

rap (ämneskategori)