Temporal winner takes all spiking neuron network sensory processing apparatus and methods
First Claim
1. A non-transitory computer-readable apparatus configured to store at least one computer process thereon, the computer process configured to detect an object in a sensory input, the computer process comprising a plurality of instructions configured to, when executed:
- based on at least one excitatory signal, generate an inhibitory signal configured to suppress generation of another excitatory signal, and thereby enable the object detection;
wherein;
the sensory input comprises a plurality of spikes associated with a first sensory modality and a second sensory modality;
the at least one excitatory signal comprising one or more pulses generated based on a portion of the sensory input comprising first representation of the object based on the first sensory modality;
the another excitatory signal comprising another one or more pulses configured to be generated based on another portion of the sensory input comprising second representation of the object based on the second sensory modality; and
the first representation of the object being characterized by a parameter having a value that is different from a value of the parameter associated with the sensory input of the first sensory modality in an area proximate to the object.
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Abstract
Apparatus and methods for contrast enhancement and feature identification. In one implementation, an image processing apparatus utilizes latency coding and a spiking neuron network to encode image brightness into spike latency. The spike latency is compared to a saliency window in order to detect early responding neurons. Salient features of the image are associated with the early responding neurons. An inhibitory neuron receives salient feature indication and provides inhibitory signal to the other neurons within an area of influence of the inhibitory neuron. The inhibition signal reduces probability of responses by the other neurons to stimulus that is proximate to the feature thereby increasing contrast within the encoded data. The contrast enhancement may facilitate feature identification within the image. Feature detection may be used for example for image compression, background removal and content distribution.
171 Citations
20 Claims
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1. A non-transitory computer-readable apparatus configured to store at least one computer process thereon, the computer process configured to detect an object in a sensory input, the computer process comprising a plurality of instructions configured to, when executed:
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based on at least one excitatory signal, generate an inhibitory signal configured to suppress generation of another excitatory signal, and thereby enable the object detection; wherein; the sensory input comprises a plurality of spikes associated with a first sensory modality and a second sensory modality; the at least one excitatory signal comprising one or more pulses generated based on a portion of the sensory input comprising first representation of the object based on the first sensory modality; the another excitatory signal comprising another one or more pulses configured to be generated based on another portion of the sensory input comprising second representation of the object based on the second sensory modality; and the first representation of the object being characterized by a parameter having a value that is different from a value of the parameter associated with the sensory input of the first sensory modality in an area proximate to the object. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method of detecting one or more salient features within an image set with a spiking neuron network, the method comprising:
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providing a first stimulus comprising a first spectral parameter of a first image of the image set to a first portion of the network; providing a second stimulus comprising a second spectral parameter of a second image of the image set to a second portion of the network; based at least in part on the provision of the first stimulus, causing generation of a plurality of pulses by the first portion of the network, the plurality of pulses encoding the first spectral parameter into a pulse latency; generating an inhibition signal based at least in part on two or more pulses of the plurality of pulses, the two or more pulses being proximate one another within a time interval; and based at least in part on the inhibition signal, suppressing responses to the second stimulus by at least one neuron of the second portion. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A spiking neuron network processing apparatus configured to process sensory input comprising at least two attributes, the apparatus comprising:
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one or more encoders configured to; receive the sensory input; and encode the sensory input to produce a plurality of pulses; a detector bank comprising one or more detectors associated with each of the at least two attributes, each of the one or more detectors configured to; receive an encoded input for an associated attribute; and based on the encoded input generate a respective feed-forward signal; and at least one inhibitory unit configured to; receive the respective feed-forward signal; in response to the received feed-forward signal, produce a feedback signal; and transmit the feedback signal to at least one of the one or more detectors; wherein the feedback signal is configured to alter a response generation parameter of at least one of the one or more detectors. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification