Myocardial mechanical function measured by cardiovascular magnetic resonance in patients with heart failure by Yufan Gao, Boxin Li, Yanhe Ma, Shuo Liang, Anhong Yu, Hong Zhang, Zhigang Guo

“…ABSTRACT: Background: Strain analysis offers a valuable tool to assess myocardial mechanics, allowing for the detection of impairments in heart function. This study aims to evaluate the pattern of myocardial strain in patients with heart failure (HF). …”
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Research on Target Detection Algorithm for Solder Joint Defects Based on the Improved YOLOv8 by Chengkai Zhang, Xiaocui Feng, Pujun Mao, Fuyan Lv

“…Secondly, the neck network of the baseline model was reconstructed and the Slide Loss function was introduced. The fusion of bidirectional cross scale connections and weighted features improved the feature extraction ability of the model and the detection accuracy of solder joint defects. …”
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SurfaceVision: An Automated Module for Surface Fault Detection in 3D Printed Products by Laukesh Kumar, Manoj Kumar Satyarthi

“…Detecting these layerwise faults is important to ensure high quality outputs. …”
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A lightweight UAV target detection algorithm based on improved YOLOv8s model by Fubao Ma, Ran Zhang, Bowen Zhu, Xirui Yang

“…Furthermore, the original loss function is replaced with SIoU to enhance detection accuracy. …”
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A lightweight algorithm for steel surface defect detection using improved YOLOv8 by Shuangbao Ma, Xin Zhao, Li Wan, Yapeng Zhang, Hongliang Gao

“…Finally, the SIoU (Simplified IoU ) is used to replace the traditional CIoU loss function, which can make the anchor frame more fast and accurate in the regression process, to improve the stability and the robustness of detection. …”
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IVP-YOLOv5: an intelligent vehicle-pedestrian detection method based on YOLOv5s by Yang Sun, Jiankun Song, Yong Li, Yi Li, Song Li, Zehao Duan

“…To reduce the error between the ground truth box and the predicted box, we apply Alpha-IoU as the bounding box loss function, improving pedestrian detection accuracy and robustness. …”
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Research on anomaly detection model for traffic time series data integrating multiple mechanisms by Peipei ZHANG, Jiaqi LIU

“…Fourthly, the modules and training strategy were combined with LSTM, while the result of the self-attention mechanism replaced the LSTM input gate, so as to optimize long sequence memory ability and reduce computing complexity. Finally, a multivariate Gaussian distribution probability function was used to discriminate anomalies. …”
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ACCDW-YOLO: an effective detection method for small-sized pests and diseases in navel oranges by Kai Wang, Youliang Chen, Hanzheng Sun

“…The incorporation of the DCNv3 module into the design creates the DCNv3-E-ELAN module, which enhances the model’s proficiency in detecting objects of varying sizes. The Wise Intersection over Union version 3 (WIoUv3) loss function was used to reduce the competitiveness of high-quality anchor boxes, reduce the harmful gradients generated by low-quality samples, and improve the overall performance of the model. …”
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Fault detection for Li-ion batteries of electric vehicles with feature-augmented attentional autoencoder by Yunsheng Fan, Zhiwu Huang, Heng Li, Wei Yuan, Lisen Yan, Yongjie Liu, Zheng Chen

“…However, in the early stages of battery failure, its manifestations are often not obvious, making it difficult for conventional algorithms to detect them in time. Thus, this paper proposes a novel fault detection framework for battery packs to reduce detection time and eliminate false alarms. …”
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SGI-YOLOv9: an effective method for crucial components detection in the power distribution network by Mianfang Yang, Bojian Chen, Chenxiang Lin, Wenxu Yao, Yangdi Li

“…This method effectively reduces the loss of fine-grained features and improves the accuracy of small objects detection by introducing the SPDConv++ downsampling module. …”
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Experiment study on UAV target detection algorithm based on YOLOv8n-ACW by Bo Xue, Bowen Zhang, Qin Cheng

“…Additionally, WIoU-V3 has been introduced as the loss function. Experiment results derived from the Visdrone2019 dataset indicate that, the YOLOv8n- ACW has achieved a 4.2% increase in mAP50(%) compared to the baseline model, while simultaneously reducing the parameter count by 36.7%, exhibiting superior capabilities in detecting small targets. …”
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Evaluation of a Deep Learning Model for Automatic Detection of Schizophrenia Using EEG Signals by Swetha Padmavathi Polisetty, Radhamani Ellapparaj, Karthikeyan M P

“…After data preprocessing to reduce noise and artifacts from EEGs, an 11-layer deep learning model consisting of convolution and LSTM layers with LeakyReLU activation function and different kernel sizes was implemented to automatically extract and classify features. …”
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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…Fourth, to improve multi-scale adaptability, we replace the standard loss function with Alpha-IoU, enhancing model robustness. …”
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Self-Powered Microsystem for Ultra-Fast Crash Detection via Prestressed Triboelectric Sensing by Yiqun Wang, Yuhan Wang, Xinzhi Liu, Xiaofeng Wang, Keren Dai, Zheng You

“…Reliable detection of high-g shocks in extreme impact scenarios, such as automobile collisions, is essential for ensuring occupant safety. …”
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Deep learning method for cucumber disease detection in complex environments for new agricultural productivity by Jun Liu, Xuewei Wang, Qian Chen, Peng Yan, Xin Liu

“…This study proposes YOLO-Cucumber, an improved lightweight detection algorithm based on YOLOv11n, incorporating four key innovations: (1) Deformable Convolutional Networks (DCN) for enhanced feature extraction of irregular targets, (2) a P2 prediction layer for fine-grained detection of early-stage lesions, (3) a Target-aware Loss (TAL) function addressing class imbalance, and (4) Channel Pruning via Batch Normalization (CPBN) for model compression. …”
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Detection and Analysis of S-Acylated Proteins via Acyl Resin–Assisted Capture (Acyl-RAC) by Dina Abdulrahman, Michael Veit

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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

“…Built on the lightweight YOLOv8n architecture, it incorporates DCNv4 modules to enhance the detection rates and reduce missed detections by effectively learning key pedestrian features. …”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. …”
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Photovoltaic panel defect detection algorithm based on infrared imaging and improved YOLOv8 by Jingdong Wang, Zhu Cheng

“…Second, GhostConv and BoTNet are incorporated into the backbone network to reduce model parameters while enhancing defect detection performance. …”
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Design and investigation of charge plasma-based TMD heterojunction TFET biosensor for ultrasensitive detection by Monika Kumari, Niraj Kumar Singh, Vinay Kantipudi, Manodipan Sahoo

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