[HTML][HTML] Data augmentation: A comprehensive survey of modern approaches
A Mumuni, F Mumuni - Array, 2022 - Elsevier
To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …
Inverse design in nanophotonics
Recent advancements in computational inverse-design approaches—algorithmic
techniques for discovering optical structures based on desired functional characteristics …
techniques for discovering optical structures based on desired functional characteristics …
Solving nonlinear equation systems based on evolutionary multitasking with neighborhood-based speciation differential evolution
Q Gu, S Li, Z Liao - Expert Systems with Applications, 2024 - Elsevier
Locating multiple roots of nonlinear equation systems (NESs) remains a challenging and
meaningful task in the numerical optimization community. Although a large number of NES …
meaningful task in the numerical optimization community. Although a large number of NES …
Affine transformation-enhanced multifactorial optimization for heterogeneous problems
Evolutionary multitasking (EMT) is a newly emerging research topic in the community of
evolutionary computation, which aims to improve the convergence characteristic across …
evolutionary computation, which aims to improve the convergence characteristic across …
Evolutionary multitasking via explicit autoencoding
Evolutionary multitasking (EMT) is an emerging research topic in the field of evolutionary
computation. In contrast to the traditional single-task evolutionary search, EMT conducts …
computation. In contrast to the traditional single-task evolutionary search, EMT conducts …
[HTML][HTML] Quality diversity: A new frontier for evolutionary computation
While evolutionary computation and evolutionary robotics take inspiration from nature, they
have long focused mainly on problems of performance optimization. Yet evolution in nature …
have long focused mainly on problems of performance optimization. Yet evolution in nature …
Multifactorial evolution: Toward evolutionary multitasking
The design of evolutionary algorithms has typically been focused on efficiently solving a
single optimization problem at a time. Despite the implicit parallelism of population-based …
single optimization problem at a time. Despite the implicit parallelism of population-based …
[PDF][PDF] Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
P Pławiak, UR Acharya - Neural Comput. Appl, 2020 - researchgate.net
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …
million persons have cardiovascular diseases around the world. Our proposed work based …
A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses
Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-
order) aerodynamic models or flight testing are some of the fundamental but complex steps …
order) aerodynamic models or flight testing are some of the fundamental but complex steps …
Multiobjective multifactorial optimization in evolutionary multitasking
In recent decades, the field of multiobjective optimization has attracted considerable interest
among evolutionary computation researchers. One of the main features that makes …
among evolutionary computation researchers. One of the main features that makes …