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Sarala Padi, Petru S. Manescu, Nicholas Schaub, Nathan Hotaling, Carl G. Simon Jr., Peter Bajcsy
Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out either
Under the new service paradigm, artificial intelligence (AI) can play a significant role in the new generation of wireless communications systems. This special issue presents a comprehensive overview of research challenges and opportunities regarding
Michael P. Majurski, Petru S. Manescu, Sarala Padi, Nicholas J. Schaub, Nathan A. Hotaling, Carl Simon Jr., Peter Bajcsy
We address the problem of segmenting cell contours from microscopy images of human induced pluripotent Retinal Pigment Epithelial stem cells (iRPE) using Convolutional Neural Networks (CNN). Our goal is to compare the accuracy gains of CNN-based
Binary classification problems include such things as classifying email messages as spam or non-spam and screening for the presence of disease (which can be seen as classifying a subject as disease-positive or disease- negative). Both Bayesian and
How to model and encode the semantics of human-written text and select the type of neural network to process it with are not settled issues in sentiment analysis. Accuracy and transferability are critical issues in machine learning in general. These
Mark Alexander Henn, Hui Zhou, Richard M. Silver, Bryan M. Barnes
Undetected patterning defects on semiconductor wafers can have severe consequences, both financially and technologically. Industry is challenged to find reliable and easy-to-implement methods for defect detection. In this paper we present robust machine
Jarrett Booz, Wei Yu, Guobin Xu, David W. Griffith, Nada T. Golmie
Accurate weather forecast is important to our daily life. Through physical atmospheric models, the weather can be accurately forecasted in a short period time. To provide weather forecast, machines learning techniques can be used for understanding and
Alice Mizrahi, thomas Marsh, Brian D. Hoskins, Mark D. Stiles
Finding the shortest path in a graph has applications to a wide range of optimization problems. However, algorithmic methods scale with the size of the graph in terms of time and energy. We propose a method to solve the shortest path problem using circuits
Sonia Buckley, Adam McCaughan, Jeff Chiles, Richard Mirin, Sae Woo Nam, Jeff Shainline
We have previously proposed a novel hardware platform for neuromorphic computing based on superconducting optoelectronics that presents many of the features necessary for information processing in the brain. Here we discuss the design and training of
Jeffrey M. Shainline, Adam N. McCaughan, Jeffrey T. Chiles, Richard P. Mirin, Sae Woo Nam, Sonia M. Buckley
We present designs of superconducting optoelectronic neurons based on superconducting single- photon detectors, Josephson junctions, semiconductor light sources, and multi-planar dielectric waveguides. The neurons send few-photon signals to synaptic
Yan Lu, Zhuo Yang, Douglas Eddy, Sundar Krishnamurty
The current AM development environment is far from being mature. Both software applications and workflow management tools are very limited due to the lack of knowledge to support engineering decision makings. AM knowledge includes design rules, operation