Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

“…Therefore, we propose the simple fall detection model (SFDM) that is computationally efficient with moderate accuracy. …”
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A Low Complexity Near-Optimal Detector Based on Teaching-Learning Algorithm for Massive MIMO by Hamid Amiriara, Mohammadreza Zahabi

“…In this paper, a low-complexity receiver is proposed using a Teaching-Learning based optimization (TLBO) heuristic algorithm for a large-scale system. …”
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Robust Miner Detection in Challenging Underground Environments: An Improved YOLOv11 Approach by Yadong Li, Hui Yan, Dan Li, Hongdong Wang

“…The Efficient Channel Attention (ECA) mechanism was integrated into the YOLOv11 model to enhance the model’s ability to focus on key features, thereby significantly improving detection accuracy. …”
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SIC based RL for massive MIMO NOMA signal detection for different modulation schemes under diverse channel conditions by Arun Kumar, Aziz Nanthaamornphong, Mohammed H. Alsharif, Mehedi Masud

“…Abstract Massive-multiple input and Multiple Outputs Non orthogonal multiple access (M-MIMO–NOMA) systems require efficient signal detection techniques to mitigate interference and enhance spectral efficiency, especially under diverse channel conditions and varying modulation schemes. …”
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YOLO-EFM: Efficient traffic flow monitoring algorithm with enhanced multi-level information fusion by Shizhou Xu, Kaidi Cui

“…Modern drones are capable of autonomously and efficiently collecting traffic images in complex environments to implement downstream detection tasks. …”
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Deep Learning-Driven Multi-Temporal Detection: Leveraging DeeplabV3+/Efficientnet-B08 Semantic Segmentation for Deforestation and Forest Fire Detection by Joe Soundararajan, Andrew Kalukin, Jordan Malof, Dong Xu

“…This study presents a deep learning framework that combines the DeepLabV3+ architecture with an EfficientNet-B08 backbone to address both deforestation and wildfire detection using satellite imagery. …”
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Improved YOLOv10 for Visually Impaired: Balancing Model Accuracy and Efficiency in the Case of Public Transportation by Rio Arifando, Shinji Eto, Tibyani Tibyani, Chikamune Wada

“…The model also exhibits reduced computational complexity and storage requirements, highlighting its efficiency. …”
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Hybrid convolutional neural network and bi-LSTM model with EfficientNet-B0 for high-accuracy breast cancer detection and classification by Umesh Kumar Lilhore, Yogesh Kumar Sharma, Brajesh Kumar Shukla, Muniraju Naidu Vadlamudi, Sarita Simaiya, Roobaea Alroobaea, Majed Alsafyani, Abdullah M. Baqasah

“…The model further enhances performance by incorporating Bi-LSTM, which allows for processing temporal dependencies in the data, which is crucial for accurately detecting complex patterns in breast cancer images. …”
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Development of a Multiplex Real-Time PCR Assay for the Detection of Eight Pathogens Associated with Bovine Respiratory Disease Complex from Clinical Samples by Fuxing Hao, Chunhao Tao, Ruilong Xiao, Ying Huang, Weifeng Yuan, Zhen Wang, Hong Jia

“…Bovine respiratory disease complex (BRDC) is one of the primary causes of morbidity, mortality, and economic loss in cattle worldwide. …”
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Reduced Complexity Initial Synchronization for 5G NR Multibeam LEO-Based Non-Terrestrial Networks by Ashish Kumar Meshram, Sumit Kumar, Jorge Querol, Stefano Andrenacci, Symeon Chatzinotas

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YOLOv8-Scm: an improved model for citrus fruit sunburn identification and classification in complex natural scenes by Guoxun Cong, Guoxun Cong, Xinghong Chen, Xinghong Chen, Zongyu Bing, Zongyu Bing, Wenhuan Liu, Wenhuan Liu, Xiangling Chen, Qun Wu, Zheng Guo, Zheng Guo, Yongqiang Zheng, Yongqiang Zheng

“…Three key enhancements are introduced: (1) DSConv module replaces the standard convolution for a more efficient and lightweight design, (2) Global Attention Mechanism (GAM) improves feature extraction for multi-scale and occluded targets, and (3) EIoU loss function enhances detection precision and generalization. …”
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HFEF²-YOLO: Hierarchical Dynamic Attention for High-Precision Multi-Scale Small Target Detection in Complex Remote Sensing by Yao Lu, Biyun Zhang, Chunmin Zhang, Yifan He, Yanqiang Wang

“…However, achieving high-precision detection of small objects against complex backgrounds remains challenging due to insufficient feature representation and background interference. …”
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Quantum-Inspired Multi-Scale Object Detection in UAV Imagery: Advancing Ultra-Small Object Accuracy and Efficiency for Real-Time Applications by Muhammad Muzammul, Muhammad Assam, Ayman Qahmash

“…Ultra-small object detection in UAV imagery presents significant challenges due to scale variation, environmental complexity, and computational constraints. …”
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An Efficient Model for Real-Time Traffic Density Analysis and Management Using Visual Graph Networks by Nikhil Nigam, Dhirendra Pratap Singh, Jaytrilok Choudhary, Surendra Solanki

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Non-orthogonal Discrete Multi-tone With Low Decoding Complexity Utilizing Symmetric Compression in Time–Frequency Space by Pengcheng Wei, Qi Sui, Zibin Li, Fan Li, Xingwen Yi, Zhaohui Li

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An FPGA Prototype for Parkinson’s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

“…This paper proposes an efficient machine learning model for PD detection using voice-based features, which offer a non-invasive, cost-effective, and accessible alternative to complex imaging methods. …”
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Analysis of China’s High-Speed Railway Network Using Complex Network Theory and Graph Convolutional Networks by Zhenguo Xu, Jun Li, Irene Moulitsas, Fangqu Niu

“…First, complex network analysis was applied to provide insights into the network’s fundamental characteristics, such as small-world properties, efficiency, and robustness. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…This segmentation method relies on acoustic anomaly detection and can markedly improve computational efficiency, facilitating deployment in environments with limited resources. …”
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Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model by Pan Zhang, Shaogui Deng, Xiyong Yuan, Fen Liu, Weibiao Xie

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Potato plant disease detection: leveraging hybrid deep learning models by Jackson Herbert Sinamenye, Ayan Chatterjee, Raju Shrestha

“…This study proposes a novel approach to improve potato plant disease detection and identification using a hybrid deep-learning model, EfficientNetV2B3+ViT. …”
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