Sentence examples for receptive layer from inspiring English sources

Even worse than the backward arrangement of the rods and cones is the fact that the blood vessels that feed the retinal sit on top of the retina between the light source and the receptive layer.

The acrylic acid-rich layer on the latex particles surface offered a large binding site for attachment of DNA capture probes to create a maximal covered surface by the DNA receptive layer.

GCE was patterned by CNTs, gold nanoparticles, and Con A to complete a receptive layer.

The neurons in the receptive or sensory layer generate a response R RF defined by Equation 8, as the calculation of Frobenious inner product of the input image S with the receptive field F of the neuron and calculation of the sum of input stimuli.

The present study elaborates on an alternative hypothesis: the blueprint for the formation of simple-cells receptive fields in layer 4, the feature maps in the cortex, and many of their inter-relationships, may reside in the layout of the retinal ganglion cell mosaics along with a simple statistical connectivity scheme between the thalamus and the cortex [29], [30].

Simple classification tasks such as the inclination of a line, circle or non-circle object and others can be performed by this type of single-layer receptive field neurons.

Like-connects-to-like connectivity was originally proposed for the superficial patch system by Mitchison and Crick (1982), as a mechanism for generating complex receptive fields in layers 2 and 3 of primary visual cortex.

Alternatively, surrounds could be created within area MT, either by horizontal connections (Allman et al. 1985), or by inhibitory connections from especially large receptive fields found in layer 5 (Raiguel et al. 1995).

These differences suggest that supra- and infragranular neurons may combine inputs in different ways, leading to varied, and likely layer-specific receptive field structure between connected neurons.

This coalesced style is motivated by an assumption that each type of convolution layer contributes different receptive field.

By utilizing LRF-RBMs with gradually increasing receptive field sizes on each layer, our LRF-DNN learns features of increasing complexity and demonstrates hierarchical part-based compositionality.