Add to ORKGWe describe the combination of neural network training and volume holographic storage technologies using photorefractive crystals for real-time image processing. Experimental results on using the system for multi-channel distortion-invariant image recognition are presented. 1
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
Photorefractive materials exhibit an interesting plasticity under the influence of an optical field....
A new approach to learning in a multilayer optical neural network based on holographically interconn...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
The capabilities of photorefractive crystals as media for holographic interconnections in neural net...
This paper describes a new optical processing devices that can handle large patterns and can accommo...
An optical computer which performs the classification of an input object pattern into one of two lea...
The dense interconnections that characterize neural networks are most readily implemented using opti...
An optical network is described that is capable of recognizing at standard video rates the identity ...
We present a novel, versatile optoelectronic neural network architecture for implementing supervised...
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We suggest a method for coding high-resolution computer-generated volume holograms. It involves spli...
Neuromorphic models are proving capable of performing complex machine learning tasks, overcoming the...
In a holographic optical learning network, the decay of multiply exposed holographic interconnection...
The ability of photorefractive crystals to holographically record an optical image in real time allo...
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
Photorefractive materials exhibit an interesting plasticity under the influence of an optical field....
A new approach to learning in a multilayer optical neural network based on holographically interconn...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
The capabilities of photorefractive crystals as media for holographic interconnections in neural net...
This paper describes a new optical processing devices that can handle large patterns and can accommo...
An optical computer which performs the classification of an input object pattern into one of two lea...
The dense interconnections that characterize neural networks are most readily implemented using opti...
An optical network is described that is capable of recognizing at standard video rates the identity ...
We present a novel, versatile optoelectronic neural network architecture for implementing supervised...
377 We describe two expriments in optical neural computing. In the first a closed optical feedback l...
We suggest a method for coding high-resolution computer-generated volume holograms. It involves spli...
Neuromorphic models are proving capable of performing complex machine learning tasks, overcoming the...
In a holographic optical learning network, the decay of multiply exposed holographic interconnection...
The ability of photorefractive crystals to holographically record an optical image in real time allo...
We describe two experiments in optical neural computing. In the first a closed optical feedback loop...
Photorefractive materials exhibit an interesting plasticity under the influence of an optical field....
A new approach to learning in a multilayer optical neural network based on holographically interconn...