Ship crack detection method based on lightweight fast convolution and bidirectional weighted feature fusion network by Chong WANG, Yuhui ZHU

“…Methods First, a lightweight convolutional structure (GSConv) is used to replace the standard convolution and introduce an attention mechanism in the backbone of YOLOv5s to achieve the reduction of network parameters and computational complexity while enhancing the ability to extract crack features. …”
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Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation by Jungpil Shin, Abu Saleh Musa Miah, Rei Egawa, Koki Hirooka, Md. Al Mehedi Hasan, Yoichi Tomioka, Yong Seok Hwang

“…Each stream employs adaptive graph-based feature aggregation and consecutive separable convolutional neural networks (Sep-TCN), significantly reducing the computational complexity and the number of parameters of the model compared to prior systems. …”
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LSTM autoencoder based parallel architecture for deepfake audio detection with dynamic residual encoding and feature fusion by Priyanka Muruganandham, Govardhana Rajan Thangasamy, Sangeetha Jayaraman, Rekha Dharmarajan

“…By integrating diverse speech features-including MFCC, temporal, prosodic, wavelet packet, and glottal parameters the model captures both low- and high-level audio characteristics. …”
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Customized Spectro-Temporal CNN Feature Extraction and ELM-Based Classifier for Accurate Respiratory Obstruction Detection by M. Muthulakshmi, K. Venkatesan, Syarifah Bahiyah Rahayu, K. L. Nayana Sree

“…The fusion of deep features from different spatiotemporal structures outperforms individual features when fed into the ELM model, resulting in clear discrimination of obstructive and restrictive respiratory diseases. …”
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An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…To address the challenges of small target scale, complex backgrounds, and excessive model parameters in existing deep learning-based power line segmentation algorithms, this paper introduces RGS-UNet, a lightweight segmentation model integrating a residual-like cross-layer feature fusion module. …”
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A Rotated Object Detection Model With Feature Redundancy Optimization for Coronary Athero-Sclerotic Plaque Detection by Xue Hao, Haza Nuzly Abdull Hamed, Qichen Su, Xin Dai, Linqiang Deng

“…These redundant features interfere with plaque feature extraction, resulting in decreased performance and increased computational complexity. …”
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Feature engineering for fault detection and diagnosis in Power Transmission Lines using a tree-based approach by Hassan N. Noura, Zaid Allal, Ola Salman, Khaled Chahine

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R-AFPN: a residual asymptotic feature pyramid network for UAV aerial photography of small targets by Zuowen Chen, Yahong Ma, Zi’an Gong, Minghao Cao, Yuyao Yang, Zhiyuan Wang, Tengjie Wang, Jing Li, Yuxi Liu

“…Abstract This study proposes an improved Residual Asymptotic Feature Pyramid Network (R-AFPN) to address challenges in small target detection from the Unmanned Aerial Vehicle (UAV) perspectives, such as scale imbalance, feature extraction difficulty, occlusion, and computational constraints. …”
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Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

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Spatial–Spectral Feature Fusion and Spectral Reconstruction of Multispectral LiDAR Point Clouds by Attention Mechanism by Guoqing Zhou, Haoxin Qi, Shuo Shi, Sifu Bi, Xingtao Tang, Wei Gong

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Construction and Application of Feature Recommendation Model for Remote Sensing Interpretation of Rock Strata Based on Knowledge Graph by Liufeng Tao, Qirui Wu, Miao Tian, Zhong Xie, Jianguo Chen, Yueyu Wu, Qinjun Qiu

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A Lightweight Intrusion Detection System with Dynamic Feature Fusion Federated Learning for Vehicular Network Security by Junjun Li, Yanyan Ma, Jiahui Bai, Congming Chen, Tingting Xu, Chi Ding

“…Experimental evaluation on the CAN-Hacking dataset shows that the proposed intrusion detection system achieves more than 99% F1 score with only 1.11 MB of memory and 81,863 trainable parameters, while maintaining low computational overheads and ensuring data privacy, which is very suitable for edge device deployment.…”
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LCFANet: A Novel Lightweight Cross-Level Feature Aggregation Network for Small Agricultural Pest Detection by Shijian Huang, Yunong Tian, Yong Tan, Zize Liang

“…The LCFANet-n model has <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2.78</mn><mi>M</mi></mrow></semantics></math></inline-formula> parameters and a computational cost of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>6.7</mn></mrow></semantics></math></inline-formula> GFLOPs, enabling lightweight deployment. …”
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Model Input-Output Configuration Search With Embedded Feature Selection for Sensor Time-Series and Image Classification by Anh Tuan Hoang, Zsolt Janos Viharos

“…Moreover, the algorithm reduced feature dimensionality to just 2&#x2013;5% of the original data, significantly enhancing computational efficiency. …”
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Physics-inspired time-frequency feature extraction and lightweight neural network for power quality disturbance classification by Zhiwen Hou, Boyu Wang, Jingrui Liu, Yumeng He, Yuxuan Yao

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Ship Target Detection in SAR Images Based on Multiple Attention Mechanism and Cross-Scale Feature Fusion by Yuwu Wang, Tieming Wu, Limin Guo, Yuhan Mo

“…This reduces the sensitivity of the CIoU loss function to positional offsets of small targets, with only a slight increase in computational and parameter costs, thereby further improving the detection accuracy of small targets. …”
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Deep TPS-PSO: Hybrid Deep Feature Extraction and Global Optimization for Precise 3D MRI Registration by Gayathri Ramasamy, Tripty Singh, Xiaohui Yuan, Ganesh R Naik

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Selection of the Binding Object on the Current Image Formed by the Technical Vision System Using Structural and Geometric Features by Sotnikov O., Sivak V., Pavlov Ya., Нashenko S., Borysenko T., Torianyk D.

“…The most significant result is the identified values of fractal dimension ranges depending on the object content of the image, as well as experimentally established noise parameters to identify the necessary features in histograms of fractal dimensions. …”
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Hybrid face recognition under adverse conditions using appearance‐based and dynamic features of smile expression by Murat Taskiran, Nihan Kahraman, Cigdem Eroglu Erdem

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