Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set of specific receptive fields. The properties of the network are detailed in this paper. Simulation results show that the network is able to perform image feature extraction within a time interval of 100 ms. This processing time is consistent with the human visual system. The demonstrations show how the network can extract right-angle contours in a visual image. Based on this principle, many other image features can be extracted by analogy. The parallel processing mechanism of this network model is very promising for a hardware implementation based on VLSI or FPGA technology.

SNN4ImageFeature_IPCAT2007-Subversion.pdf

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．