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Radar Image Segment...
Radar Image Segmentation using Second-Order Recurrent Networks
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- Ziemke, Tom (författare)
- Högskolan i Skövde,Institutionen för datavetenskap,The Connectionist Research Group
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(creator_code:org_t)
- Skövde : University of Skövde, 1996
- Engelska.
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Serie: IDA Technical Reports ; HS-IDA-TR-96-008
- Relaterad länk:
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https://urn.kb.se/re...
Abstract
Ämnesord
Stäng
- 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)