Radar Image Segmentation using Recurrent Artificial Neural Networks

• This paper discusses the application of artificial neural networks to the segmentation of Doppler radar images, in particular the detection of oil spills within sea environments, based on a classification of radar backscatter signals. Best results have been achieved with recurrent backpropagation networks of an architecture similar to that of Elman's Simple Recurrent Network. The recurrent networks are shown to be very robust to variations in both sea state (weather conditions) as well as illumination distance, and their performance is analysed in further detail.

• HS-IDA-TR-96-001Annotation: In Pattern Recognition Letters, 17, 319-334, special issue 'Computer Vision Applications of Artificial Neural Networks', Elsevier Science, May 1996.

Subject headings

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

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

Keyword

oil spill detection

radar image segmentation

recurrent artificial neural networks

Computer and systems science

Data- och systemvetenskap

Publication and Content Type

vet (subject category)

rap (subject category)