Publications (8)
An Introduction to Artificial Prediction Markets for Classification
Adrian Barbu, Nathan Lay
Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets…
Face Detection with a 3D Model
Adrian Barbu, Nathan Lay, Gary Gramajo
This paper presents a part-based face detection approach where the spatial relationship between the face parts is represented by a hidden 3D model with six parameters. The computat…
Using YOLO v7 to Detect Kidney in Magnetic Resonance Imaging
Pouria Yazdian Anari, Fiona Obiezu, Nathan Lay +16
Introduction This study explores the use of the latest You Only Look Once (YOLO V7) object detection method to enhance kidney detection in medical imaging by training and testing a…
Random Hinge Forest for Differentiable Learning
Nathan Lay, Adam P. Harrison, Sharon Schreiber +2
We propose random hinge forests, a simple, efficient, and novel variant of decision forests. Importantly, random hinge forests can be readily incorporated as a general component wi…
The Artificial Regression Market
Nathan Lay, Adrian Barbu
The Artificial Prediction Market is a recent machine learning technique for multi-class classification, inspired from the financial markets. It involves a number of trained market…
Spatial Aggregation of Holistically-Nested Convolutional Neural Networks for Automated Pancreas Localization and Segmentation
Holger R. Roth, Le Lu, Nathan Lay +4
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, the pancreas demonstrates ver…