A New Feature Extraction Method for Bearing Faults in Impulsive Noise Using Fractional Lower-Order Statistics by Qianqian Xu, Kai Liu

“…According to the performance degradation problem of feature extraction from higher-order statistics in the context of alpha-stable noise, a new feature extraction method is proposed. …”
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Online Degradation Feature Extraction of Shore Bridge Gearbox based on Morphological Fractal and Sliding Window Weibull Fitting by Dejian Sun, Xiong Hu, Bing Wang, Wei Wang, Jichang Lin

“…In order to solve the degenerative feature extraction issue of hoisting mechanism gearbox, an online extraction method for degeneration feature based on mathematical morphological fractal dimension and sliding window Weibull fitting is proposed. …”
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Classification of Prominent Cacao Pod Diseases Using Multi-Feature Visual Analysis and k-Nearest Neighbors Algorithm by Earl Clarence San Diego, Seph Gerald Rodrin, Edwin Arboleda

“…The machine training model was preceded with visual feature extraction of color and texture parameters representing the cacao pod samples. …”
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A Novel Stacking Heterogeneous Ensemble Model with Hybrid Wrapper-Based Feature Selection for Reservoir Productivity Predictions by Changlin Zhou, Lang Zhou, Fei Liu, Weihua Chen, Qian Wang, Keliang Liang, Wenqiu Guo, Liying Zhou

“…Therefore, this study developed a stacking heterogeneous ensemble model with a hybrid wrapper-based feature selection strategy to forecast reservoir productivity, resolve the overfitting problem, and improve productivity prediction. …”
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RaHFF-Net: Recall-Adjustable Hierarchical Feature Fusion Network for Remote Sensing Image Change Detection by Bin Wang, Kang Zhao, Tong Xiao, Pinle Qin, Jianchao Zeng

“…To address aforementioned problem, we propose a high recall multiscale feature fusion model for RS change interpretation. …”
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A Fast Method of Feature Extraction for Lowering Vehicle Pass-By Noise Based on Nonnegative Tucker3 Decomposition by Haijun WANG, Guo CHENG, Guoyong DENG, Xueping LI, Honggeng LI, Yuanyi HUANG

“…In order to cope with this problem, a new method, with the antinoise ability of the algorithm on the condition by which the features are entangled, is developed to extract clear features for the fault analysis. …”
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A Lightweight Multi-Frequency Feature Fusion Network with Efficient Attention for Breast Tumor Classification in Pathology Images by Hailong Chen, Qingqing Song, Guantong Chen

“…This paper proposes a lightweight breast tumor classification model with multi-frequency feature fusion (LMFM) to tackle the problem of inadequate feature extraction and poor classification performance. …”
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Feature Enhancement of TUM-RGBD Depth Images and Performance Evaluation of Gaussian Splatting-Based SplaTAM Method by Ali Furkan Kamanlı, Cemil Zeyveli

“…However, the depth images in the TUM-RGBD dataset are of lower quality than other datasets. This problem negatively affects the depth data's accuracy and reduces the quality of mapping results. …”
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A weighted pattern matching approach for classification of imbalanced data with a fireworks-based algorithm for feature selection by N. K. Sreeja

“…Learning a classifier from imbalanced data is a challenging problem in Machine learning. A dataset is said to be imbalanced when the number of instances belonging to one class is much less than the number of instances belonging to the other class. …”
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Bearing fault diagnosis algorithm based on maximum correlated kurtosis feature mode decomposition and compound Gini index by YANG Gang, XU Wuyi, DENG Qin, QIN Limu, WEI Yuqian

“…The maximum correlated kurtosis feature mode decomposition (MCKFMD) method can effectively remove redundant information and enhance fault features, but its effect is affected by the number of decomposition modes, the number of initialized filters and the filter length. …”
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Enhancing convergence speed with feature enforcing physics-informed neural networks using boundary conditions as prior knowledge by Mahyar Jahani-nasab, Mohamad Ali Bijarchi

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Extraction and Recognition of Color Feature in true Color Images Using Neural Network Based on Colored Histogram Technique by Orjuwan Aljawadi

“…The importance of this research is based on developing the ability of (BPNN) in images ‘objects recognition based on color feature that is very important feature in artificial intelligence and colored image processing fields from developing the systems of alarms robots in fire recognition , medical digenesis of tumors, certain pattern’s recognition in different segments of an image , face and eyes’ iris recognition as a part of security systems , it helps solve the problem of limitation of recognition process in neural networks in many fields.…”
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Efficient GDD feature approximation based brain tumour classification and survival analysis model using deep learning by M. Vimala, SatheeshKumar Palanisamy, Sghaier Guizani, Habib Hamam

“…The problem of brain tumor classification (BTC) has been approached with several methods and uses different features obtained from MRI brain scans. …”
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A Genetic Algorithm and PCA-Based Feature Selection to Improve the Failure Diagnosis Performance of Railway Vehicle Doors by Gil Hyun Kang, Ho Cheol Ki, Sang Hyun An, Juhee Choi, Chul Su Kim

“…A principal component analysis-based feature dimensional reduction with explained variance ratio was used to reduce the effect from multi-collinearity of features. …”
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NMS-KSD: Efficient Knowledge Distillation for Dense Object Detection via Non-Maximum Suppression and Feature Storage by Suho Son, Byung Cheol Song

“…The core of NMS-KSD is the integration of Non-Maximum Suppression (NMS) and channel max pooling to effectively select and store key features from the teacher model’s intermediate feature maps. …”
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Bayesian Neural Networks With Robust Feature Interpretation for Enhanced Compressive Strength Prediction of Ultra‐High‐Performance Concrete by Tao Zhang, Ji Hao, Jie Zhang, Lina Du, Yunhao Zhang, Wenbin Jiao

“…A novel dataset comprising 799 UHPC mix designs, featuring 15 input parameters and one target variable, was curated from the literature. …”
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An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds by Ya He, Kun Feng, Minghui Hu, Jinmiao Cui

“…The compressive sensing (CS) theory provides a new slight to the big-data problem led by the Shannon sampling theorem in rolling element bearings condition monitoring, where the measurement matrix of CS tends to be designed by the random matrix (RM) to preserve the integrity of signal roughly. …”
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Research on land desertification in Ejin Banner from 1991 to 2021 based on Albedo-MSAVI feature space model by Xiaofang Jiang

“…This suggests that the feature space is suitable for research on desertification land classification in the area. …”
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FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning by Meng Zhang, Jiankun Ma, Zhenxi Zhang, Feng Zhou

“…To address the critical challenges of high data privacy leakage risks, excessive communication overhead, and data silos in automatic modulation recognition tasks, this paper proposes a federated automatic modulation recognition method based on characteristic feature fine-tuning (FedeAMR-CFF). Specifically, the clients extract representative features through distance-based metric screening, and the server aggregates model parameters via the FedAvg algorithm and fine-tunes the model using the collected features. …”
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HierbaNetV1: a novel feature extraction framework for deep learning-based weed identification by Justina Michael, Thenmozhi Manivasagam

“…Originality is brought by addressing the problem of varying-sized region of interest (ROI) in an image by extracting features using diversified filters. …”
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