Case of Acute Graft Failure during Suspected Humoral Rejection with Preserved Ejection Fraction, but Severely Reduced Longitudinal Deformation Detected by 2D-Speckle Tracking by Tor Skibsted Clemmensen, Hans Eiskjær, Pernille B. Kofoed-Nielsen, Søren Høyer, Steen Hvitfeldt Poulsen

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Time Series Anomaly Detection Using Signal Processing and Deep Learning by Jana Backhus, Aniruddha Rajendra Rao, Chandrasekar Venkatraman, Chetan Gupta

“…In the second step, we utilize a Functional Neural Network Autoencoder for anomaly detection, leveraging its ability to capture non-linear temporal relationships in the data. …”
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DVCW-YOLO for Printed Circuit Board Surface Defect Detection by Pei Shi, Yuyang Zhang, Yunqin Cao, Jiadong Sun, Deji Chen, Liang Kuang

“…Next, within the neck structure, the C2f module is substituted with the more lightweight VOVGSCSP module, thereby reducing model redundancy, simplifying model complexity, and enhancing detection speed. …”
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A One-Stage HMDV Algorithm Applied in Multitarget Detection in SAR Images by Lei Pang, Weihe Huang, Fengli Zhang, Yinhong Song

“…Finally, to resolve the issue of low detection performance due to the small proportion of small targets in the prediction boxes, a new width and height vector loss function is proposed. …”
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An Improved Bird Detection Method Using Surveillance Videos from Poyang Lake Based on YOLOv8 by Jianchao Ma, Jiayuan Guo, Xiaolong Zheng, Chaoyang Fang

“…Second, we redesign a feature fusion network, termed the DyASF-P2, which enhances the network’s ability to capture small object features and reduces the target information loss. Third, a lightweight detection head is designed to effectively reduce the model’s size without sacrificing the precision. …”
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A Real-Time Cotton Boll Disease Detection Model Based on Enhanced YOLOv11n by Lei Yang, Wenhao Cui, Jingqian Li, Guotao Han, Qi Zhou, Yubin Lan, Jing Zhao, Yongliang Qiao

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AHN-YOLO: A Lightweight Tomato Detection Method for Dense Small-Sized Features Based on YOLO Architecture by Wenhui Zhang, Feng Jiang

“…The key innovations of AHN-YOLO include (1) the introduction of an ADown module to reduce model parameters; (2) the adoption of a Normalized Wasserstein Distance (NWD) loss function to stabilize small-feature detection; and (3) the proposal of a lightweight hybrid attention mechanism, Light-ES, to enhance focus on disease regions. …”
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Research on X-Ray Weld Defect Detection of Steel Pipes by Integrating ECA and EMA Dual Attention Mechanisms by Guanli Su, Xuanhe Su, Qunkai Wang, Weihong Luo, Wei Lu

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A Deep Learning-Based Method for Detection of Multiple Maneuvering Targets and Parameter Estimation by Beiming Yan, Yong Li, Qianlan Kou, Ren Chen, Zerong Ren, Wei Cheng, Limeng Dong, Longyuan Luan

“…Drones, with their small radar cross-sections and high maneuverability, cause range migration (RM) and Doppler frequency migration (DFM), which complicate the use of traditional radar methods and reduce detection accuracy. Furthermore, the detection of multiple targets exacerbates the issue, as target interference complicates detection and impedes parameter estimation. …”
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Using hyperspectral reflectance to detect changes in photosynthetic activity in Atractylodes chinensis leaves as a function of decreasing soil water content by J. LIU, Y. WANG, X.M. LIN, Z.C. XUE, F.R. ZENG

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The association of serum hsa-miR-21-5p expression with the severity and prognosis of heart failure with reduced ejection fraction by Lingmiao Wang, Ailin Guo, Shuang Liang, Lingling Yu, Bai Shen, Zhihang Huang

“…RT-qPCR was used for the detection of serum hsa-miR-21-5p levels. Whether serum hsa-miR-21-5p expression correlated to cardiac function and hemodynamic indicators was evaluated using Spearman correlation analysis. …”
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Colony-YOLO: A Lightweight Micro-Colony Detection Network Based on Improved YOLOv8n by Meihua Wang, Junhui Luo, Kai Lin, Yuankai Chen, Xinpeng Huang, Jiping Liu, Anbang Wang, Deqin Xiao

“…Based on the MBCD, a colony detection model named Colony-YOLO is proposed. Firstly, the lightweight backbone network StarNet is employed, aiming to enhance feature extraction capabilities while reducing computational complexity. …”
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High Incidence of Moderately Reduced Renal Function and Lead Bioaccumulation in Agricultural Workers in Assin South District, Ghana: A Community-Based Case-Control Study by Patrick Adu, Eric Kumah Forkuo, Abubakari Issah, Isaac Owusu Asumadu, Emmanuel Cadman-Sackey, Augustina A. A. Quarshie, Sampson Gyabaa, Richard K. D. Ephraim

“…Additionally, 18.1% of cases were classified as having moderately reduced renal function compared to only 6.6% of controls. …”
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Electrochemically reduced graphene oxide integrated with carboxylated-8-carboxamidoquinoline: A platform for highly sensitive voltammetric detection of Zn(II) ion by screen-printed... by Ling Ling Tan, Nur Syamimi Mohamad, Nurul Izzaty Hassan, Choo Ta Goh

“…Clinical investigations have testified to its beneficial effects on respiratory health and its deficiency may reduce immune function. A highly sensitive detection of Zn(II) ion via differential pulse voltammetry (DPV) utilizing an environmentally friendly modified screen-printed carbon electrode (SPCE) of electrochemically reduced graphene oxide (ErGO) embedded with carboxylated-8-carboxamidoquinoline (CACQ) as Zn(II) chelating ligand. …”
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An Optimized FPGA-Based FDIR System for Sensor Fault Detection in Satellite Attitude Estimation by Xianliang Chen, Zhicheng Xie, Jiashu Wu, Xiaofeng Wu

“…To solve this problem, a Fault Detection, Isolation, and Recovery (FDIR) was proposed, which integrates an adaptive unscented Kalman filter (AUKF), a radial basis function (RBF) neural network for fault detection, and a QUEST-based estimator. …”
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A Highly Stable Electrochemical Sensor Based on a Metal–Organic Framework/Reduced Graphene Oxide Composite for Monitoring the Ammonium in Sweat by Yunzhi Hua, Junhao Mai, Rourou Su, Chengwei Ma, Jiayi Liu, Cong Zhao, Qian Zhang, Changrui Liao, Yiping Wang

“…Ammonium ions (NH₄⁺) in sweat serve as indicators of metabolic function, muscle fatigue, and kidney health. Although current ion-selective all-solid-state printed sensors based on nanocomposites typically exhibit good sensitivity (~50 mV/log [NH₄⁺]), low detection limits (LOD ranging from 10⁻⁶ to 10⁻⁷ M), and wide linearity ranges (from 10⁻⁵ to 10⁻¹ M), few have reported the stability test results necessary for their integration into commercial products for future practical applications. …”
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A detection algorithm for small surface floating objects based on improved YOLOv5s by Xusheng YUE, Jun LI, Yaohong WANG, Penghao ZHU, Zhexing WANG, Xuanhao XU

“…Third, the CBAM (Convolutional Block Attention Module) was incorporated into the backbone network to address the limited feature extraction capability for detecting floating bottles on the water surface. Finally, the Normalized Wasserstein Distance (NWD) regression loss function was introduced and combined with the IoU loss function in a weighted manner to construct a comprehensive regression loss function, further enhancing detection accuracy for floating bottles on the water surface.ResultsExperimental results show that the proposed algorithm achieves a mAP@0.5 of 95.7% in detecting floating bottles on the water surface. …”
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TomatoGuard-YOLO: a novel efficient tomato disease detection method by Xuewei Wang, Jun Liu

“…The framework introduces two key innovations: the Multi-Path Inverted Residual Unit (MPIRU), which enhances multi-scale feature extraction and fusion, and the Dynamic Focusing Attention Framework (DFAF), which adaptively focuses on disease-relevant regions, substantially improving detection robustness. Additionally, the incorporation of the Focal-EIoU loss function refines bounding box matching accuracy and mitigates class imbalance. …”
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Quality-Aware PPG-Based Blood Pressure Classification for Energy-Efficient Trustworthy BP Monitoring Devices With Reduced False Alarms by Yalagala Sivanjaneyulu, M. Sabarimalai Manikandan, Srinivas Boppu, Linga Reddy Cenkeramaddi

“…Early detection of hypertension (HT) is crucial for significantly reducing the risk of serious health complications, which demands continuous or long-term blood pressure (BP) monitoring to ensure the timely management of hypertension. …”
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Deep Learning Strategy for UAV-Based Multi-Class Damage Detection on Railway Bridges Using U-Net with Different Loss Functions by Yong-Hyoun Na, Doo-Kie Kim

“…The results showed that the U-Net model trained with IoU Loss outperformed the others in terms of detection accuracy. When applied to field inspection scenarios, this approach demonstrates strong potential for objective and precise damage detection. …”
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