3.4k citations · 5.9k across the 11 of their papers we have counts for
11 papers
An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set
Ali Ismail-Fawaz, Angus Dempster, Chang Wei Tan +8
The measurement of progress using benchmarks evaluations is ubiquitous in computer science and machine learning. However, common approaches to analyzing and presenting the results…
InceptionTime: Finding AlexNet for Time Series Classification
Hassan Ismail Fawaz, Benjamin Lucas, Germain Forestier +7
This paper brings deep learning at the forefront of research into Time Series Classification (TSC). TSC is the area of machine learning tasked with the categorization (or labelling…
Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +2
Purpose: Manual feedback from senior surgeons observing less experienced trainees is a laborious task that is very expensive, time-consuming and prone to subjectivity. With the num…
Automatic alignment of surgical videos using kinematic data
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +3
Over the past one hundred years, the classic teaching methodology of "see one, do one, teach one" has governed the surgical education systems worldwide. With the advent of Operatio…
Adversarial Attacks on Deep Neural Networks for Time Series Classification
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +2
Time Series Classification (TSC) problems are encountered in many real life data mining tasks ranging from medicine and security to human activity recognition and food safety. With…
Deep Neural Network Ensembles for Time Series Classification
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber +2
Deep neural networks have revolutionized many fields such as computer vision and natural language processing. Inspired by this recent success, deep learning started to show promisi…