ESL-YOLO: Small Object Detection with Effective Feature Enhancement and Spatial-Context-Guided Fusion Network for Remote Sensing by Xiangyue Zheng, Yijuan Qiu, Gang Zhang, Tao Lei, Ping Jiang

“…This model includes: (1) an innovative plug-and-play feature enhancement module that incorporates multi-scale local contextual information to bolster detection performance for small objects; (2) a spatial-context-guided multi-scale feature fusion framework that enables effective integration of shallow features, thereby minimizing spatial information loss; and (3) a local attention pyramid module aimed at mitigating background noise while highlighting small object characteristics. …”
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Multi-convolutional neural network brain image denoising study based on feature distillation learning and dense residual attention by Huimin Qu, Haiyan Xie, Qianying Wang

“…The FPB performs feature fusion. Experimental results on brain image datasets and ground-based open datasets show that the proposed model outperforms existing methods in several metrics, and helps to improve the accuracy of brain disease diagnosis and treatment.…”
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A KWS System for Edge-Computing Applications with Analog-Based Feature Extraction and Learned Step Size Quantized Classifier by Yukai Shen, Binyi Wu, Dietmar Straeussnigg, Eric Gutierrez

“…The filter bank is behaviorally modeled, making use of second-order band-pass transfer functions, simulating the analog front-end (AFE) processing. …”
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Advancing Early Diagnosis: Predicting Mild Cognitive Impairment Progression in Normal Individuals Using Deep Learning on MRI Features by Abdullah Baktash, Yashar Sarbaz, Saeed Meshgini, Reza Afrouzian

“…This research aims to develop a deep learning-based system that efficiently identifies and analyzes the progression from Cognitively Normal (CN) to MCI, addressing the growing need for more accessible, accurate diagnostic tools. The proposed model comprises two distinct feature extraction paths to capture local and global image features. …”
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Prediction of BTEX concentrations in the air of Southern East Azerbaijan province, Iran using ensemble machine learning and feature analysis by Mansour Baziar, Negar Jafari, Ali Oghazyan, Amir Mohammadi, Ali Abdolahnejad, Ali Behnami

“…Based on R-squared values, the top-performing models identified were XGBRegressor, AdaBoostRegressor, and ExtraTreesRegressor. …”
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Parametric Analysis on Seismic Performance of Hybrid Precast Concrete Beam-Column Joint by H.-K. Choi

“…In this paper, a nonlinear finite element (FE) analysis of high-performance hybrid system (HPHS) beam-column connections is presented. …”
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Visual language transformer framework for multimodal dance performance evaluation and progression monitoring by Lei Chen

“…We propose a novel transformer-based visual-language framework for multi-modal dance performance evaluation and progression monitoring. Our approach addresses two core challenges: the learning of feature representations for complex dance movements synchronized with music across diverse styles, genres, and expertise levels, and capturing the multi-task nature of dance performance evaluation. …”
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Blind Infrared Remote-Sensing Image Deblurring Algorithm via Edge Composite-Gradient Feature Prior and Detail Maintenance by Xiaohang Zhao, Mingxuan Li, Ting Nie, Chengshan Han, Liang Huang

“…In this paper, we propose a novel blind deblurring model based on the MAP framework that leverages Composite-Gradient Feature (CGF) variations in edge regions after image blurring. …”
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Multi-Modal Feature Set-Based Detection of Freezing of Gait in Parkinson’s Disease Patients Using SVM by Ghulam Murtaza, Mohammed Hammoud, Andrey Somov

“…Then, time-, frequency-, and time-frequency-based features were extracted and fed to the Support Vector Machine (SVM) model. …”
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Resolution-Aware Deep Learning with Feature Space Optimization for Reliable Identity Verification in Electronic Know Your Customer Processes by Mahasak Ketcham, Pongsarun Boonyopakorn, Thittaporn Ganokratanaa

“…The model also demonstrated strong robustness against noise and image blur, maintaining reliable performance even under challenging input conditions. …”
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Smartphone-derived multidomain features including voice, finger-tapping movement and gait aid early identification of Parkinson’s disease by Wee-Shin Lim, Sung-Pin Fan, Shu-I Chiu, Meng-Ciao Wu, Pu-He Wang, Kun-Pei Lin, Yung-Ming Chen, Pei-Ling Peng, Jyh-Shing Roger Jang, Chin-Hsien Lin

“…An integrated multimodal model using a support vector machine improved performance to 0.86 and achieved 0.82 for identifying early-stage PD during the “off” phase. …”
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DSCnet: detection of drug and alcohol addiction mechanisms based on multi-angle feature learning from the hybrid representation of EEG by Jing Wu, Nan Zhang, Qilei Ye, Xiaorui Zheng, Minmin Shao, Xian Chen, Hui Huang

“…On the UCI alcohol addiction dataset, it achieved 84.56% accuracy, 84.73% precision, 84.56% recall, and 84.63% F1-score.DiscussionThese results outperform existing models and demonstrate a balanced performance across both datasets, highlighting DSCnet's potential in addiction detection.…”
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A dynamic attention mechanism for road extraction from high-resolution remote sensing imagery using feature fusion by Haoming Bai, Chao Ren, Zhenzhong Huang, Yao Gu

“…The dual-branch encoder leverages dual convolutions and multi-head deep convolutions to extract fundamental features and capture fine-grained details. The feature fusion module integrates both global and local information, enhancing the model’s ability to represent features effectively. …”
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External validation of SpineNetV2 on a comprehensive set of radiological features for grading lumbosacral disc pathologies by Alemu Sisay Nigru, MSc, Sergio Benini, PhD, Matteo Bonetti, MD, Graziella Bragaglio, MSc, Michele Frigerio, MD, Federico Maffezzoni, MSc, Riccardo Leonardi, PhD

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Stereo Matching Network with Transformer-CNN Feature Fusion and ConvGRU Refinement for High-resolution Satellite Stereo Images by M. Yang, S. Jiang, W. Jiang, Q. Li

“…This paper proposes an end-to-end model for high-resolution satellite remote sensing images. …”
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Detection of abnormal tourist behavior in scenic spots based on optimized Gaussian model for background modeling by Liu Xiaohua

“…Based on this model, an ABD method was established using action data based on spatio-temporal block detection and motion foreground effect map features. …”
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Dual-Branch Neural Network-Based In-Loop Filter for VVC Intra Coding Using Spatial-Frequency Feature Fusion by Zhen Feng, Xu Liu, Cheolkon Jung

“…Since each has different types of information, directly concatenating all these inputs for the network may cause mutual interference between the input data and decrease the model performance. In this paper, we propose a dual-branch NNLF for VVC intra coding using spatial-frequency feature fusion. …”
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Elitism-based multi-objective differential evolution with extreme learning machine for feature selection: a novel searching technique by Subrat Kumar Nayak, Pravat Kumar Rout, Alok Kumar Jagadev, Tripti Swarnkar

“…Twenty-one benchmark datasets have been considered for performance evaluation. Moreover, the selected feature subsets are tested using 10-fold cross-validation. …”
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BiDFNet: A Bidirectional Feature Fusion Network for 3D Object Detection Based on Pseudo-LiDAR by Qiang Zhu, Yaping Wan

“…The proposed model addresses key challenges in multimodal 3D detection by introducing three novel components: (1) the SAF-Conv module, which extends the receptive field through improved submanifold sparse convolution, enhancing feature extraction from pseudo-point clouds while effectively reducing edge noise; (2) the bidirectional cross-modal attention feature interaction module (BiCSAFIM), which employs a multi-head cross-attention mechanism to enable global information interaction between point cloud and image features; and (3) the attention-based feature fusion module (ADFM), which adaptively fuses dual-stream features to improve robustness. …”
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Cyber intrusion detection using ensemble of deep learning with prediction scoring based optimized feature sets for IOT networks by Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Vaishali H. Kamble

“…To address these issues, we propose the Ensemble of Deep Learning Models with Prediction Scoring-based Optimized Feature Sets (EDLM-PSOFS). …”
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