18 citations · 18 across the 3 of their papers we have counts for
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In situ fine-tuning of in silico trained Optical Neural Networks
Gianluca Kosmella, Ripalta Stabile, Jaron Sanders
Optical Neural Networks (ONNs) promise significant advantages over traditional electronic neural networks, including ultrafast computation, high bandwidth, and low energy consumpti…
Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs
Lorenzo Pes, Maryam Dehbashizadeh Chehreghan, Rick Luiken +3
This work evaluates a forward-only learning algorithm on the MNIST dataset with hardware-in-the-loop training of a 4f optical correlator, achieving 87.6% accuracy with O(n2) comple…
Noise-Resilient Designs for Optical Neural Networks
Gianluca Kosmella, Ripalta Stabile, Jaron Sanders
All analog signal processing is fundamentally subject to noise, and this is also the case in modern implementations of Optical Neural Networks (ONNs). Therefore, to mitigate noise…