A scalable optical convolutional neural network (SOCNN) based on free-space optics and Koehler illumination was proposed to address the limitations of the previous 4f correlator system. Unlike Abbe illumination, Koehler illumination provides more uniform illumination and reduces crosstalk. The SOCNN allows for scaling of the input array and the use of incoherent light sources. Hence, the problems associated with 4f correlator systems can be avoided. We analyzed the limitations in scaling the kernel size and parallel throughput and found that the SOCNN can offer a multilayer convolutional neural network with massive optical parallelism
Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more impor...
Convolutional Neural Networks (CNNs) are fundamental machine learning tools to process image, speech...
Convolutional neural networks are paramount in image and signal processing including the relevant cl...
Convolutional neural networks (CNNs) represent one of the most effective methods for image classific...
Convolutional layers are a critical feature of modern neural networks and require significant com-pu...
In the past decade, machine learning techniques, in particular artificial neural networks (ANNs), h...
The convolution neural network (CNN) is a classical neural network with advantages in image processi...
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. Storing, proceßing...
The explosive growth of computation and energy cost of artificial intelligence has spurred strong in...
An optical convolutional neural network is demonstrated in which linear operations are implemented b...
Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and ...
Several experimental demonstrations of neural networks using coherent optics are demonstrated. An as...
Convolutions are one of the most relevant operations in artificial intelligence (AI) systems. High c...
Diffractive optical neural networks (DONNs) have emerged as a promising optical hardware platform fo...
Convolutional neural network (CNN) is one of the best neural network structures for solving classifi...
Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more impor...
Convolutional Neural Networks (CNNs) are fundamental machine learning tools to process image, speech...
Convolutional neural networks are paramount in image and signal processing including the relevant cl...
Convolutional neural networks (CNNs) represent one of the most effective methods for image classific...
Convolutional layers are a critical feature of modern neural networks and require significant com-pu...
In the past decade, machine learning techniques, in particular artificial neural networks (ANNs), h...
The convolution neural network (CNN) is a classical neural network with advantages in image processi...
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. Storing, proceßing...
The explosive growth of computation and energy cost of artificial intelligence has spurred strong in...
An optical convolutional neural network is demonstrated in which linear operations are implemented b...
Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and ...
Several experimental demonstrations of neural networks using coherent optics are demonstrated. An as...
Convolutions are one of the most relevant operations in artificial intelligence (AI) systems. High c...
Diffractive optical neural networks (DONNs) have emerged as a promising optical hardware platform fo...
Convolutional neural network (CNN) is one of the best neural network structures for solving classifi...
Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more impor...
Convolutional Neural Networks (CNNs) are fundamental machine learning tools to process image, speech...
Convolutional neural networks are paramount in image and signal processing including the relevant cl...