Evolutionary Platform for Retargetable Image Processing Applications
from Theoretical Neural Networks to Real-Time Applications
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This work presents a cognitive information processing on an evolutionary platform for retargetable applications such as facial image recognition, image feature extraction, evolvable filters, and environmental information tracking. Cognitive processing can process multiple-sensory information on an automated system such as an unmanned vehicle or a surveillance unit in a remote site to avoid harsh terrain. Evolutionary platform supports the ability to change information processing behavior to comply with ever changing environment in order to accomplish a mission objective. The cognitive processi...
This work presents a cognitive information
processing on an evolutionary platform for
retargetable applications such as facial image
recognition, image feature extraction, evolvable
filters, and environmental information tracking.
Cognitive processing can process multiple-sensory
information on an automated system such as an
unmanned vehicle or a surveillance unit in a remote
site to avoid harsh terrain. Evolutionary platform
supports the ability to change information
processing behavior to comply with ever changing
environment in order to accomplish a mission
objective. The cognitive processing model can
overcome particular difficulties to traditional
search, exploration, and engineering decision making
applications. The proposed cognitive strategies
emphasize the decomposition of multi-sensory
information, the re-construction of internal
representations, and the cognitive processing of
combined information which yield sub-optimal
solutions and indicate best local system direction.
Several applications, such as facial image
recognition and digital signal processing, are used
to verify our models and compare them with other
well-known approaches.
processing on an evolutionary platform for
retargetable applications such as facial image
recognition, image feature extraction, evolvable
filters, and environmental information tracking.
Cognitive processing can process multiple-sensory
information on an automated system such as an
unmanned vehicle or a surveillance unit in a remote
site to avoid harsh terrain. Evolutionary platform
supports the ability to change information
processing behavior to comply with ever changing
environment in order to accomplish a mission
objective. The cognitive processing model can
overcome particular difficulties to traditional
search, exploration, and engineering decision making
applications. The proposed cognitive strategies
emphasize the decomposition of multi-sensory
information, the re-construction of internal
representations, and the cognitive processing of
combined information which yield sub-optimal
solutions and indicate best local system direction.
Several applications, such as facial image
recognition and digital signal processing, are used
to verify our models and compare them with other
well-known approaches.
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