Underwater image enhancement via multiscale disentanglement strategy by Jiaquan Yan, Hao Hu, Yijian Wang, Muhammad Wasim Nawaz, Naveed Ur Rehman Junejo, Ente Guo, Huibin Feng

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LPCF-YOLO: A YOLO-Based Lightweight Algorithm for Pedestrian Anomaly Detection with Parallel Cross-Fusion by Peiyi Jia, Hu Sheng, Shijie Jia

“…Additionally, an ADown module is introduced in the third layer to reduce the computational cost. In the neck network, a Lightweight High-level Screening Feature Pyramid Network (L-HSFPN) is designed to replace the PAFPN structure. …”
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Short-term PV power prediction based on meteorological similarity days and SSA-BiLSTM by Yikang Li, Wei Huang, Keying Lou, Xizheng Zhang, Qin Wan

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Facial morphology prediction after complete denture restoration based on principal component analysis by Cheng Cheng, Xiaosheng Cheng, Ning Dai, Tao Tang, Zhenteng Xu, Jia Cai

“…Firstly, the curvature feature template with few feature points is constructed to replace the deformed areas of facial models. …”
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A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…Moreover, to conserve computational resources, a lightweight CED module was introduced to reduce parameters and conserve the computing resources of the UAV. …”
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An Improved Small Target Detection Algorithm Based on YOLOv8s by G. Ma, C. Xu, Z. Xu, X. Song

“…First, the S_C2f_CAFM module is integrated into the feature extraction network, enabling the effective capture of fine-grained local features and broad contextual information, while simultaneously reducing model parameters and computational complexity. …”
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Generating Human-Interpretable Rules from Convolutional Neural Networks by Russel Pears, Ashwini Kumar Sharma

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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

“…In the feature fusion part, a feature modulation block processes multi-scale features by synergistically combining global and local information, thereby reducing redundant computations and decreasing both parameter count and computational complexity to achieve model lightweighting. …”
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DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…Our system achieves superior results compared to existing models using a self-constructed smoking detection dataset, reducing computational complexity by 23.20% while trimming the model parameters by 33.95%. …”
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An Innovative Inversion Method of Potato Canopy Chlorophyll Content Based on the AFFS Algorithm and the CDE-EHO-GBM Model by Xiaofei Yang, Qiao Li, Honghui Li, Hao Zhou, Jinyan Zhang, Xueliang Fu

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ADMNet: adaptive deformable convolution large model combining multi-level progressive fusion for Building Change Detection by Liye Mei, Haonan Yu, Zhaoyi Ye, Chuan Xu, Cheng Lei, Wei Yang

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A Novel Transformer-Based Multiscale Siamese Framework for High-Resolution Remote Sensing Change Detection by Liangjun Wang, Weitao Chen, Haoyi Wang, Zhengchao Chen

“…Notably, compared to that of five multiscale-based methods, our proposed TMSF achieves superior performance while requiring only half the number of parameters and computational cost. Thus, the proposed model demonstrates a marked advancement in remote sensing CD. …”
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An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

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Highly efficient stacking ensemble learning model for automated keratoconus screening by Zahra J. Muhsin, Rami Qahwaji, Ibrahim Ghafir, Mo’ath AlShawabkeh, Muawyah Al Bdour, Saif Aldeen AlRyalat, Majid Al-Taee

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RFAG-YOLO: A Receptive Field Attention-Guided YOLO Network for Small-Object Detection in UAV Images by Chengmeng Wei, Wenhong Wang

“…To address these challenges, we propose the receptive field attention-guided YOLO (RFAG-YOLO) method, an advanced adaptation of YOLOv8 tailored for small-object detection in UAV imagery, with a focus on improving feature representation and detection robustness. To this end, we introduce a novel network building block, termed the receptive field network block (RFN block), which leverages dynamic kernel parameter adjustments to enhance the model’s ability to capture fine-grained local details. …”
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Balancing Precision and Speed: Introducing the Performance Efficiency Evaluation Ratio (PEER) in Visual Odometry by Cem Atilgan, Muharrem Mercimek

“…To address this limitation, we propose the Performance Efficiency Evaluation Ratio (PEER), a novel, adaptive, and lightweight metric that jointly evaluates algorithm performance based on both fidelity and computation time. PEER incorporates a tunable weighting parameter to prioritize performance, speed, or a balanced trade-off, and employs normalization techniques to ensure comparability across different algorithms and systems. …”
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Enhancing Object Detection in Underground Mines: UCM-Net and Self-Supervised Pre-Training by Faguo Zhou, Junchao Zou, Rong Xue, Miao Yu, Xin Wang, Wenhui Xue, Shuyu Yao

“…We propose the ESFENet backbone network, incorporating a Global Response Normalization (GRN) module to enhance feature capture stability while employing depthwise separable convolutions and HGRNBlock modules to reduce parameter volume and computational complexity. …”
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Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms by Manal Abdullah Alohali, Sultan Alahmari, Mohammed Aljebreen, Mashael M. Asiri, Achraf Ben Miled, Sami Saad Albouq, Othman Alrusaini, Ali Alqazzaz

“…It impacts a vast amount of computers. Researchers have proposed numerous malware detection solutions for the past few years. …”
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Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…In addition, the detection performance is superior to other traditional detection models under the condition of low parameter quantities and computational complexity. …”
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An advanced fire detection system for assisting visually challenged people using recurrent neural network and sea-horse optimizer algorithm by Fahd N. Al-Wesabi, Abeer A. K. Alharbi, Ishfaq Yaseen

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