Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

“…In addition, the need for comprehensive train detection including pantograph-catenary systems and running gears, lead to an increased number of on-board devices, resulting in fewer computational resources available for each detection system, and complicating equipment installation and maintenance. …”
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A review of deep learning models to detect malware in Android applications by Elliot Mbunge, Benhildah Muchemwa, John Batani, Nobuhle Mbuyisa

“…Smartphone applications use permissions to allow users to utilize different functionalities, making them susceptible to malicious software (malware). …”
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Realizing depth measurement and edge detection based on a single metasurface by Yang Siwen, Wei Qunshuo, Zhao Ruizhe, Li Xin, Zhang Xue, Li Yao, Li Junjie, Jing Xiaoli, Li Xiaowei, Wang Yongtian, Huang Lingling

“…Double helix point source function is utilized, and three verification experiments are carried out, including double-helix beam calibration, 2D object and 3D object detection, respectively. …”
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Enhanced object detection in low-visibility haze conditions with YOLOv9s. by Yang Zhang, Bin Zhou, Xue Zhao, Xiaomeng Song

“…Furthermore, the implementation of a nonmonotonic strategy for dynamically adjusting the loss function weights significantly boosts the model's detection precision and training efficiency. …”
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PA-YOLO-Based Multifault Defect Detection Algorithm for PV Panels by Wang Yin, Zhao Jingyong, Xie Gang, Zhao Zhicheng, Hu Xiao

“…For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. …”
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Myoglobin expression improves T-cell metabolism and antitumor effector function by Haifeng C Xu, Diran Herebian, Ertan Mayatepek, Dirk Brenner, Aleksandra A Pandyra, Philipp A Lang, Sascha Dietrich, Julia Werner, Georgios Theodorakis, Ichiro Katahira, Mitrajit Ghosh, Michal Gorzkiewicz, Luisa de Sousa Santos, Ann Kathrin Bergmann, Max Anstötz, Anne Busch, Carsten Berndt

“…Although T cells expressing Mb exhibited increased expression of effector cytokines, PD-1 was still detected and targetable by anti-PD-1 monoclonal antibodies, which in combination with transfer of Mb-expressing T cells demonstrated maximal efficacy in delaying tumor growth.Conclusion Taken together, we show that expression of Mb in T cells can increase their metabolism, infiltration into the tumor tissue, and effector function against cancer cells.…”
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Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling by C. D. Jiménez‐Rodríguez, G. Fabiani, R. Schoppach, K. Mallick, S. J. Schymanski, M. Sulis

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Research on Underwater Target Detection Technology Based on SMV-YOLOv11n by Dongcheng Liao, Yijun Shen, Jinyu Ou, Yanlian Du

“…High-precision underwater object detection is a crucial component for improving the efficiency of marine resource development. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features by Daniel Hilário da Silva, Caio Tonus Ribeiro, Leandro Rodrigues da Silva Souza, Adriano Alves Pereira

“…Seventeen ML algorithms were applied to a dataset of voice recordings from Healthy Control and PD individuals, sourced from a publicly available repository. We leveraged the PyCaret Python library's ML algorithms and functions, which were introduced in this article, to demonstrate their simplicity and effectiveness in dealing with real-world data. …”
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3L-YOLO: A Lightweight Low-Light Object Detection Algorithm by Zhenqi Han, Zhen Yue, Lizhuang Liu

“…Existing methods often use image enhancement to improve detection, which results in a large amount of computational resource consumption. …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…Ensuring high accuracy and efficiency in foreign object intrusion detection along railway lines is critical for guaranteeing railway operational safety under limited resource conditions. …”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…These optimizations enable efficient deployment on resource-constrained mobile devices, making the model highly suitable for real-time disease detection in practical agricultural scenarios where hardware limitations are critical. …”
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Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…IntroductionIn the aviation field, drone search and rescue is a highly urgent task involving small target detection. In such a resource-constrained scenario, there are challenges of low accuracy and high computational requirements.MethodsThis paper proposes IYFVMNet, an improved lightweight detection network based on YOLOv8. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…Finally, the Inner-IoU optimization loss function is applied to accelerate model convergence and enhance detection accuracy.ResultsTesting results indicate that SGSNet performs exceptionally well across key metrics, achieving 98.83% precision, 99.45% recall, 99.14% F1 score, 99.50% mAP@0.5, and a loss value of 0.3534. …”
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New groups of highly divergent proteins in families as old as cellular life with important biological functions in the ocean by Duncan Sussfeld, Romain Lannes, Eduardo Corel, Guillaume Bernard, Pierre Martin, Eric Bapteste, Eric Pelletier, Philippe Lopez

“…Results Here, we used an iterative, network-based approach for remote homology detection, to probe a dataset of 40 million ORFs predicted in marine environments. …”
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Integrated Functional Analysis of the Nuclear Proteome of Classically and Alternatively Activated Macrophages by John E. Wiktorowicz, Imran H. Chowdhury, Susan Stafford, Subhadip Choudhuri, Nilay Dey, Nisha J. Garg

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ChiMSource improves the accuracy of studies on novel amino acid sequences by predicting alternative sources of mass spectrometry-derived peptides by Umut Çakır, Noujoud Gabed, Ali Yurtseven, Igor Kryvoruchko

“…Here, we present a highly flexible program that predicts alternative chimeric and non-chimeric sources of peptides detected by MS proteomics.…”
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