6 citations · 6 across the 3 of their papers we have counts for
13 papers
On the performance of deep learning for numerical optimization: an application to protein structure prediction
Hojjat Rakhshani, Lhassane Idoumghar, Soheila Ghambari +2
Deep neural networks have recently drawn considerable attention to build and evaluate artificial learning models for perceptual tasks. Here, we present a study on the performance o…
Bypassing or flying above the obstacles? A novel multi-objective UAV path planning problem
Mahmoud Golabi, Soheila Ghambari, Julien Lepagnot +3
This study proposes a novel multi-objective integer programming model for a collision-free discrete drone path planning problem. Considering the possibility of bypassing obstacles…
From feature selection to continuous optimization
Hojjat Rakhshani, Lhassane Idoumghar, Julien Lepagnot +1
Metaheuristic algorithms (MAs) have seen unprecedented growth thanks to their successful applications in fields including engineering and health sciences. In this work, we investig…
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…