Online multi‐object tracking based on time and frequency domain features by Mahbubeh Nazarloo, Meisam Yadollahzadeh‐Tabari, Homayun Motameni

“…The modified cuckoo optimization algorithm is utilized for feature selection, which has the ability such as fast convergence and global optima finding. …”
Get full text

Key risk factors of generalized anxiety disorder in adolescents: machine learning study by Yonghwan Moon, Hyekyung Woo, Hyekyung Woo

“…Predictive models using Random Forest and Artificial Neural Networks demonstrated that the XGBoost feature selection method effectively identified key factors and showed strong performance. …”
Get full text

Fault Diagnosis Method for Rotating Machinery Based on Hierarchical Amplitude-Aware Permutation Entropy and Pairwise Feature Proximity by Ling Shu, Jinxing Shen, Xiaoming Liu

“…Combined with the pairwise feature proximity (PWFP) feature selection method and gray wolf algorithm optimization support vector machine (GWO-SVM), a new intelligent fault diagnosis method for rotating machinery is proposed. …”
Get full text

AquaYOLO: Enhancing YOLOv8 for Accurate Underwater Object Detection for Sonar Images by Yanyang Lu, Jingjing Zhang, Qinglang Chen, Chengjun Xu, Muhammad Irfan, Zhe Chen

“…In addition, we introduce Dynamic Selection Aggregation Module (DSAM) and Context-Aware Feature Selection (CAFS) in the neck network. These modifications allow AquaYOLO to capture intricate details better and reduce feature redundancy, leading to improved performance in underwater object detection tasks. …”
Get full text

Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks by Reham Abdallah, Sayed Abdelgaber, Hanan Ali Sayed

“…The researchers adopt the Analytic Hierarchy Process (AHP) for feature selection and integrated transfer learning to boost the accuracy of the study’s predictions. …”
Get full text

Federated Learning-Based Load Forecasting for Energy Aggregation Service Providers by HUANG Yichuan, SONG Yuhui, JING Zhaoxia

“…First，an artificial neural network with multidimensional environmental feature selection is established according to the task requirements. …”
Get full text

Content-Based Image Retrieval Using Colour, Gray, Advanced Texture, Shape Features, and Random Forest Classifier with Optimized Particle Swarm Optimization by Manoharan Subramanian, Velmurugan Lingamuthu, Chandran Venkatesan, Sasikumar Perumal

“…These extracted features are processed in various levels like removing redundancy by optimal feature selection and fusion by optimal weighted linear combination. …”
Get full text

Anticipating Stock Market of the Renowned Companies: A Knowledge Graph Approach by Yang Liu, Qingguo Zeng, Joaquín Ordieres Meré, Huanrui Yang

“…The proposed model and other feature selection models were used to perform feature extraction on the websites of Thomson Reuters and Cable News Network. …”
Get full text

MultiPhys: Heterogeneous Fusion of Mamba and Transformer for Video-Based Multi-Task Physiological Measurement by Chaoyang Huo, Pengbo Yin, Bo Fu

“…Additionally, a gate is utilized for feature selection, which classifies the features of different physiological indicators. …”
Get full text

Sensor selection scheme in activity recognition based on hierarchical feature reduction by Yu Wei, Libin Jiao, Jie Sha, Jixin Ma, Anton Umek, Anton Kos

“…It divides the process of feature reduction into two stages: first, redundant sensors are removed with one-order sequential forward selection based on mutual information; second, feature selection strategy that maximizing class-relevance is integrated with low-dimensional mapping so that the set of features will be further compressed. …”
Get full text

Fault Diagnosis for Reducer via Improved LMD and SVM-RFE-MRMR by Xiaoguang Zhang, Zhenyue Song, Dandan Li, Wei Zhang, Zhike Zhao, Yingying Chen

“…Due to degradation of fault diagnosis methods resulting from redundant features, a novel feature selection method combining SVM-RFE with MRMR is proposed to select salient features, improving the performance of fault diagnosis approach. …”
Get full text

A Hybrid Approach of Using Wavelets and Fuzzy Clustering for Classifying Multispectral Florescence In Situ Hybridization Images by Yu-Ping Wang, Ashok Kumar Dandpat

“…In comparison with conventional algorithms, the wavelet-based approaches offer more advantages such as the adaptive feature selection and accurate image registration. The algorithms have been tested on images from normal cells, showing the improvement in classification accuracy. …”
Get full text

Feature Extraction and Selection Scheme for Intelligent Engine Fault Diagnosis Based on 2DNMF, Mutual Information, and NSGA-II by Peng-yuan Liu, Bing Li, Cui-e Han, Feng Wang

“…Then a novel feature extraction technique, named two-dimensional nonnegative matrix factorization, is employed for characterizing the time-frequency representations. In the feature selection phase, a hybrid filter and wrapper scheme based on mutual information and NSGA-II is utilized to acquire a compact feature subset for engine fault diagnosis. …”
Get full text

Development of Vision Based Multiview Gait Recognition System with MMUGait Database by Hu Ng, Wooi-Haw Tan, Junaidi Abdullah, Hau-Lee Tong

“…The extracted features are normalized with linear scaling, which is followed by feature selection prior to the classification process. …”
Get full text

Ensemble learning-based predictor for driver synonymous mutation with sequence representation. by Chuanmei Bi, Yong Shi, Junfeng Xia, Zhen Liang, Zhiqiang Wu, Kai Xu, Na Cheng

“…EPEL combines five tree-based models and optimizes feature selection to enhance predictive accuracy. Notably, the incorporation of DNA shape features and deep learning-derived features from chemical molecule represents a pioneering effect in assessing the impact of synonymous mutations in cancer. …”
Get full text

A New Comprehensive Framework for Identifying and Monitoring the Interseasonal Characteristics of Meteorological Drought by Hamza Amin, Rizwan Niaz, Nafisa A. Albasheir, Fuad S. Al-Duais, Mohammed M. A. Almazah, A. Y. Al-Rezami

“…Besides, the Monte Carlo feature selection (MCFS) is applied to select more important stations from the varying clusters. …”
Get full text

A sparrow search algorithm based hybrid meta-heuristic algorithm for population growth rate prediction by Milad Shahvaroughi Farahani, Hamed Farrokhi-Asl Farrokhi-Asl, Ghazal Ghasemi

“…A set of 18 economic indicators serves as input variables, and a Genetic Algorithm (GA) is used for feature selection. The data used for analysis spans the most recent ten years and is presented on a monthly basis. …”
Get full text

Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…We use the SHAP feature selection technique to improve the detection procedure. …”
Get full text

Charge Diagnostics and State Estimation of Battery Energy Storage Systems Through Transformer Models by Rolando Antonio Gilbert Zequera, Anton Rassolkin, Toomas Vaimann, Ants Kallaste

“…Filter, Wrapper, and Embedded methods are the techniques implemented to achieve Feature Selection and illustrate Key Performance Indicators (KPIs) in battery testing. …”
Get full text

Remaining Useful Life Prediction of Turbofan Engine in Varied Operational Conditions Considering Change Point: A Novel Deep Learning Approach with Optimum Features by Subrata Rath, Deepjyoti Saha, Subhashis Chatterjee, Ashis Kumar Chakraborty

“…This paper aims (i) to identify the change point in RUL trends and patterns (ii) to select the most relevant features, and (iii) to predict RUL with the selected features and identified change points. A two-stage feature-selection algorithm was developed, followed by a change point identification mechanism, and finally, a Bidirectional Long Short-Term Memory (BiLSTM) model was designed to predict RUL. …”
Get full text