A survey on evolutionary multiobjective feature selection in classification: approaches, applications, and challenges
Maximizing the classification accuracy and minimizing the number of selected features are
two primary objectives in feature selection, which is inherently a multiobjective task …
two primary objectives in feature selection, which is inherently a multiobjective task …
Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …
MATR: Multimodal medical image fusion via multiscale adaptive transformer
Owing to the limitations of imaging sensors, it is challenging to obtain a medical image that
simultaneously contains functional metabolic information and structural tissue details …
simultaneously contains functional metabolic information and structural tissue details …
Forecasting stock market for an efficient portfolio by combining XGBoost and Hilbert–Huang transform
A Dezhkam, MT Manzuri - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Portfolio formation in financial markets is the task of not taking non-necessary risks.
Quantitative investment powered by machine learning has opened many new opportunities …
Quantitative investment powered by machine learning has opened many new opportunities …
An improved loop subdivision to coordinate the smoothness and the number of faces via multi-objective optimization
Abstract 3D mesh subdivision is essential for geometry modeling of complex surfaces, which
benefits many important applications in the fields of multimedia such as computer animation …
benefits many important applications in the fields of multimedia such as computer animation …
Design of concrete incorporating microencapsulated phase change materials for clean energy: A ternary machine learning approach based on generative adversarial …
The inclusion of microencapsulated phase change materials (MPCM) in construction
materials is a promising solution for increasing the energy efficiency of buildings and …
materials is a promising solution for increasing the energy efficiency of buildings and …
A kernel correlation-based approach to adaptively acquire local features for learning 3D point clouds
Abstract 3D models are used in a variety of CAX fields, and their key is 3D data geometry
and semantic perception. However, semantic learning of 3D point clouds is a challenge due …
and semantic perception. However, semantic learning of 3D point clouds is a challenge due …
A binary individual search strategy-based bi-objective evolutionary algorithm for high-dimensional feature selection
Evolutionary computation is promising in tackling with the feature selection problem, but still
has poor performance in obtaining good feature subset in high-dimensional problems. In …
has poor performance in obtaining good feature subset in high-dimensional problems. In …
CSITime: Privacy-preserving human activity recognition using WiFi channel state information
Human activity recognition (HAR) is an important task in many applications such as smart
homes, sports analysis, healthcare services, etc. Popular modalities for human activity …
homes, sports analysis, healthcare services, etc. Popular modalities for human activity …
Spatial-driven features based on image dependencies for person re-identification
T Si, F He, H Wu, Y Duan - Pattern Recognition, 2022 - Elsevier
Person re-identification (Re-ID) aims to search for the same pedestrian in different cameras,
which is a crucial research direction in pattern recognition. Recent deep learning methods …
which is a crucial research direction in pattern recognition. Recent deep learning methods …