AI-assistance for predictive maintenance of renewable energy systems

Real-world application of machine-learning-based fault detection trained with experimental data

(2020) Gerrit Bode et al.   ENERGY

CNN based automatic detection of photovoltaic cell defects in electroluminescence images

(2019) M. Waqar Akram et al.   ENERGY

Global levelised cost of electricity from offshore wind

(2019) Jonathan Bosch et al.   ENERGY

Artificial Intelligence and Big Data in Public Health

(2018) Kurt Benke et al.   International Journal of Environmental Research and Public Health

Early fault detection and diagnosis in bearings for more efficient operation of rotating machinery

(2017) Aleksandar Brkovic et al.   ENERGY

Detection and compensation of anomalous conditions in a wind turbine

(2017) S. Hur et al.   ENERGY

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

What can machine learning do? Workforce implications

(2017) Erik Brynjolfsson et al.   SCIENCE

Adapting to Artificial Intelligence

(2016) Saurabh Jha et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

(2016) Varun Gulshan et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

A novel prognostic model of performance degradation trend for power machinery maintenance

(2014) Dengji Zhou et al.   ENERGY

Factors influencing decision support system acceptance

(2012) Rania Shibl et al.   DECISION SUPPORT SYSTEMS

The Insidious Problem of Fatigue in Medical Imaging Practice

(2011) Bruce I. Reiner et al.   JOURNAL OF DIGITAL IMAGING

Computer-aided Diagnosis: How to Move from the Laboratory to the Clinic

(2011) Bram van Ginneken et al.   RADIOLOGY

Does computer-aided clinical decision support improve the management of acute abdominal pain? A systematic review

(2010) J. G. Cooper et al.   EMERGENCY MEDICINE JOURNAL

Computer-aided detection (CAD) as a second reader using perspective filet view at CT colonography: effect on performance of inexperienced readers

(2009) V.A. Fisichella et al.   CLINICAL RADIOLOGY