Automatic Feature Engineering-Based Optimization Method for Car Loan Fraud Detection by Jian Yang, Zixin Tang, Zhenkai Guan, Wenjia Hua, Mingyu Wei, Chunjie Wang, Chenglong Gu

“…Compared with traditional automatic feature engineering methods, the number of features and training time are reduced by 92.5% and 54.3%, respectively, whereas accuracy is improved by 23%. …”
Get full text

Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data by Daniel Scheliga, Patrick Mäder, Marco Seeland

“…Additionally, shared raw data fingerprints can directly leak sensitive visual information, in certain cases even resembling the original client training data. To alleviate these problems, we propose a Feature-based dataset FingerPrinting mechanism (FFP). …”
Get full text

An object detection method in foggy weather based on novel feature enhancement and fusion by ZHU Lei, ZHAO Han, WANG Weili

“…Additionally, coordinate attention was introduced in the feature fusion module to accurately locate object during training and reduce the loss of object feature information. …”
Get full text

Data-Efficient Bone Segmentation Using Feature Pyramid- Based SegFormer by Naohiro Masuda, Keiko Ono, Daisuke Tawara, Yusuke Matsuura, Kentaro Sakabe

“…These enhancements enable better image feature extraction and more precise object contour detection, which is particularly beneficial for medical imaging applications with limited training data.…”
Get full text

Diabetic Retinopathy Detection Using DL-Based Feature Extraction and a Hybrid Attention-Based Stacking Ensemble by Sanjana Rajeshwar, Shreya Thaplyal, Anbarasi M., Siva Shanmugam G.

“…Our proposed hybrid model combines image processing and machine learning (ML) strengths, leveraging discriminative abilities and custom features. The methodology involves data acquisition from a diverse dataset, data augmentation to enrich training data, and a multistep image processing pipeline. …”
Get full text

Steganographer identification of JPEG image based on feature selection and graph convolutional representation by Qianqian ZHANG, Yi ZHANG, Hao LI, Yuanyuan MA, Xiangyang LUO

“…Aiming at the problem that the feature dimension of JPEG image steganalysis is too high, which leads to the complexity of distance calculation between users and a decrease in the identification performance of the steganographer, a method for steganographer recognition based on feature selection and graph convolutional representation was proposed.Firstly, the steganalysis features of the user’s images were extracted, and the feature subset with highseparability was selected.Then, the users were represented as a graph, and the features of users were obtained by training the graph convolutional neural network.Finally, because inter-class separability and intra-class aggregation were considered, the features of users that could capture the differences between users were learned.For steganographers who use JPEG steganography, such as nsF5, UED, J-UNIWARD, and so on, to embed secret information in images, the proposed method can reduce the feature dimensions and computing.The identification accuracy of various payloads can reach more than 80.4%, and it has an obvious advantage at the low payload.…”
Get full text

Steganographer identification of JPEG image based on feature selection and graph convolutional representation by Qianqian ZHANG, Yi ZHANG, Hao LI, Yuanyuan MA, Xiangyang LUO

“…Aiming at the problem that the feature dimension of JPEG image steganalysis is too high, which leads to the complexity of distance calculation between users and a decrease in the identification performance of the steganographer, a method for steganographer recognition based on feature selection and graph convolutional representation was proposed.Firstly, the steganalysis features of the user’s images were extracted, and the feature subset with highseparability was selected.Then, the users were represented as a graph, and the features of users were obtained by training the graph convolutional neural network.Finally, because inter-class separability and intra-class aggregation were considered, the features of users that could capture the differences between users were learned.For steganographers who use JPEG steganography, such as nsF5, UED, J-UNIWARD, and so on, to embed secret information in images, the proposed method can reduce the feature dimensions and computing.The identification accuracy of various payloads can reach more than 80.4%, and it has an obvious advantage at the low payload.…”
Get full text

Terrain relative navigation based on deep feature template matching and visual odometry by E. V. Rulko

Get full text

Efficient Learning-Based Robotic Navigation Using Feature-Based RGB-D Pose Estimation and Topological Maps by Eder A. Rodríguez-Martínez, Jesús Elías Miranda-Vega, Farouk Achakir, Oleg Sergiyenko, Julio C. Rodríguez-Quiñonez, Daniel Hernández Balbuena, Wendy Flores-Fuentes

“…Robust indoor robot navigation typically demands either costly sensors or extensive training data. We propose a cost-effective RGB-D navigation pipeline that couples feature-based relative pose estimation with a lightweight multi-layer-perceptron (MLP) policy. …”
Get full text

Quantitative evaluation of college music teaching pronunciation based on nonlinear feature extraction by Wang Aiping

“…To quantitatively evaluate the quality of music pronunciation, this work proposes a method for extracting nonlinear features of music signals. By selecting different styles of music signals, based on chaos theory, fractal theory, and Lyapunov exponent, the change in correlation dimension of different kinds of music signals is analyzed from a nonlinear perspective, so as to realize vocal music evaluation and training in music teaching. …”
Get full text

Multiple-Fault Diagnosis Method Based on Multiscale Feature Extraction and MSVM_PPA by Min Zhang, Zhenyu Cai, Wenming Cheng

Get full text

Dynamic analysis of malicious behavior propagation based on feature selection in software network by Huajian Xue, Huajian Xue, Yali Wang, Qiguang Tang

“…This paper introduces a dynamic analysis detection method for malicious behavior based on feature extraction (MBDFE), designed to effectively identify and thwart the spread of malicious software. …”
Get full text

Feature selection‐based android malware adversarial sample generation and detection method by Xiangjun Li, Ke Kong, Su Xu, Pengtao Qin, Daojing He

“…Using the frequency differential enhancement feature selection algorithm to perform feature screening, the algorithm forms two different feature sets and establishes two different training sets to train different classification algorithms. …”
Get full text

Dynamic Node Privacy Feature Decoupling Graph Autoencoder Based on Attention Mechanism by Yikai Huang, Jinchuan Tang, Shuping Dang

Get full text

Perceptual Quality Assessment for Pansharpened Images Based on Deep Feature Similarity Measure by Zhenhua Zhang, Shenfu Zhang, Xiangchao Meng, Liang Chen, Feng Shao

“…Therefore, this paper proposes a perceptual quality assessment method based on deep feature similarity measure. The proposed network includes spatial/spectral feature extraction and similarity measure (FESM) branch and overall evaluation network. …”
Get full text

Non-intrusive load monitoring based on time-enhanced multidimensional feature visualization by Tie Chen, Yimin Yuan, Jiaqi Gao, Shinan Guo, Pingping Yang

“…Based on this, this paper proposes a non-intrusive load monitoring method based on time-enhanced multidimensional feature visualization. …”
Get full text

Categorization of Celebrity Photos Based on Deep Machine Learning for Feature Extraction and Classification by Salwa Shakir Baawi, Farah Jawad Al-Ghanim, Nisreen Ryadh Hamza

“…This paper aims to analyze celebrity categorization based on deep features under different conditions. …”
Get full text

Fleet formation identification and analyzing method based on disposition feature for remote sensing by Fangli Mou, Zide Fan, Chuan’ao Jiang, Keqing Zhu, Lei Wang, Xinming Li

“…This study introduces an effective fleet formation identification and analysis method based on disposition features for remote sensing. …”
Get full text

Employee Turnover Prediction Model Based on Feature Selection and Imbalanced Data Handling by Yuan Fang, Zhongqiu Zhang

“…Results showed that the RF model, trained on GAN-balanced data and using RFE-selected only five features, achieved the best performance with an accuracy of 0.98, precision of 0.98, recall of 0.92, F1-score of 0.95, and Cohen’s Kappa of 0.94. …”
Get full text

Mask suitability recommendation based on facial image key feature dimension recognition by Xinjin YANG, Weiqun XIE, Zhenyu HUANG, Yixiong SHEN, Lin YE, Hai LI, Zhuobo YANG, Zhu LIAO, Simi LI

“…ObjectiveTo develop a mask suitability correlation model based on facial features extracted from facial images using facial recognition technology, enabling rapid mask recommendations for users and reducing infection risk. …”
Get full text