Third Ventricle Width Measurements Based on YOLO and Localized Intensity Features by Xiao Zhou, Ao Wan, Xingang Mou, Hongling Gao, Zheng Xue

“…Firstly, to solve the problem of third ventricle detection in the complex background of TCS images, the YOLO-TV improvement model is proposed to improve the detection accuracy. …”
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Multi-Channel Fusion Decision-Making Online Detection Network for Surface Defects in Automotive Pipelines Based on Transfer Learning VGG16 Network by Jian Song, Yingzhong Tian, Xiang Wan

“…In order to improve the detection efficiency and reduce the amount of data transmission and processing, an improved ROI detection algorithm for surface defects is proposed. …”
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Quantification of oleanolic acid and apigenin in biological matrices following intraperitoneal administration of co-loaded nanoformulations: Method validation and biodistribution s... by Amna Naz, Sadia Haider, Mavra Rana, Neelum Malik, Attia Afzal, Muhammad Farooq, Muhammad Sarfraz

“…The validated HPLC-UV bioanalytical method was effectively applied in quantification, stability, and pharmacokinetic studies of co-loaded nanoformulations of OA and APG with particle size 163 nm. The entrapment efficiency for OA was 93.95 ± 3.50 %, and for APG, it was 94.5 ± 2.31 % in combined nanoformulation, establishing it as a promising analytical technique for detecting these anticancer agents in complex matrices such as blood, plasma, and polymeric systems.…”
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Fault location and isolation technology for power grid automation based on intelligent algorithms by Qi Guo, Fuhe Wang, Suxia Cheng, Ke Wang, Yifan Zhang

“…As power grids become more complex, intelligent algorithms are critical for improving the efficiency of fault localization and isolation. …”
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From mechanism to applications: Advanced microneedles for clinical medicine by Yuqing Yang, Haifu Sun, Xiao Sun, Yu Wang, Fan Xu, Wenyu Xia, Liang Chen, Manyi Li, Tianke Yang, Yusen Qiao, Dechun Geng

“…In light of the potential limitations of conventional drug delivery, including low drug bioavailability and insufficient therapeutic efficiency, as well as the financial burden and discomfort associated with conventional detection, there is a thirst for alternatives. …”
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Investigation of the pathogenic potential and the possibility of cross-species transmission of H5 avian influenza viruses detected on the territory of the Russian Federation in 201... by Nikolay G. Zinyakov, Alena D. Grekhneva, Artem V. Andriyasov, Evgeniya V. Ovchinnikova, Nelli A. Guseva, Anton A. Kozlov, Zoya B. Nikonova, Pavel D. Zhestkov, Dmitry B. Andreychuk, Ilya A. Chvala

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DualHet-YOLO: A Dual-Backbone Heterogeneous YOLO Network for Inspection Robots to Recognize Yellow-Feathered Chicken Behavior in Floor-Raised House by Yaobo Zhang, Linwei Chen, Hongfei Chen, Tao Liu, Jinlin Liu, Qiuhong Zhang, Mingduo Yan, Kaiyue Zhao, Shixiu Zhang, Xiuguo Zou

“…Meanwhile, it reduces model parameters by 14.6% and computational complexity by 29.2%, achieving a synergistic optimization of accuracy and efficiency. …”
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TECHNOLOGICAL INNOVATIONS FOR TREATMENT OF CASINGS by Vera V. Eveleva, Tatyana M. Cherpalova, Elena A. Shipovskaya

“…It was established that minimum effective concentration of solutions of technological aids for treatment of casings corresponds to concentration of the solution with maximum adsorption of the resulting complexes on the surface of the liquid-air phase boundary. …”
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Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

“…ABSTRACT Detection of faults in solar photovoltaic (PV) systems is an important concern to guarantee that renewable energy source generation keeps its efficiency and reliability. …”
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A recognition model for winter peach fruits based on improved ResNet and multi-scale feature fusion by Yan Li, Chunping Li, Tingting Zhu, Shurong Zhang, Li Liu, Zhanpeng Guan

“…The results show that the WinterPeachNet model achieves excellent performance in the winter peach detection task, with P = 0.996, R = 0.996, mAP50 = 0.995, and mAP50-95 = 0.964, demonstrating the model’s efficiency and accuracy in the winter peach detection task. …”
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Microplastics in soil: a comprehensive review of analytical techniques by Sedat Gündoğdu, Muhittin Onur Akça, Mehmet Gursoy, Murat Yılmaz, Xiaoyu Zhang, Xiaoyu Zhang, Andrés Rodríguez-Seijo, Andrés Rodríguez-Seijo, Aisha Bibi, Maria Luisa Di Gioia, Milica Velimirovic

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Identification of leaves of wild Ussurian Pear (Pyrus ussuriensis) based on YOLOv10n-MCS by Niman Li, Niman Li, Xingguang Dong, Yongqing Wu, Luming Tian, Ying Zhang, Hongliang Huo, Dan Qi, Jiayu Xu, Chao Liu, Zhiyan Chen, Yulu Mou

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Performance Evaluation of YOLOv11 and YOLOv12 Deep Learning Architectures for Automated Detection and Classification of Immature Macauba (<i>Acrocomia aculeata</i>) Fruits by David Ribeiro, Dennis Tavares, Eduardo Tiradentes, Fabio Santos, Demostenes Rodriguez

“…Inference throughput averaged 3.9 ms per image for YOLOv11x and 6.7 ms for YOLOv12x, highlighting a trade-off between speed and architectural complexity. Fused model representations revealed optimized layer fusion and reduced computational overhead (GFLOPs), facilitating efficient deployment. …”
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An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction by Ahmed Hadded, Mossaad Ben Ayed, Shaya A. Alshaya

“…Notably, the findings presented in this work are based exclusively on comprehensive simulations using COMSOL and MATLAB, as no physical prototypes or biomarker detection experiments were conducted. The SiNW-FET biosensor, functionalized with antibodies specific to viral antigens, detects impedance shifts caused by antibody–antigen interactions, providing a highly sensitive platform for viral detection. …”
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Underwater Side-Scan Sonar Target Detection: An Enhanced YOLOv11 Framework Integrating Attention Mechanisms and a Bi-Directional Feature Pyramid Network by Junhui Zhu, Houpu Li, Min Liu, Guojun Zhai, Shaofeng Bian, Ye Peng, Lei Liu

“…To address these issues, this paper proposes the ABFP-YOLO model, which was designed to enhance the accuracy of underwater target detection. Specifically, the bi-directional feature pyramid network (BiFPN) structure is integrated into the model to efficiently fuse the features of different scales, significantly improving the capability of the network to recognize targets of varying scales, especially small targets in complex scenarios. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…These limitations include the complexity of the models and their poor ability to generalize. …”
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An enzyme-free electrochemical biosensor for sensitive and specific detection of microRNA-21 based on target recycling amplification and non-linear hybridization chain reaction by Jing Guo, Shou-feng Zhao, Shuang Chen, Wei-qing Song, Li-qun Li

“…Abstract A novel electrochemical biosensor with high amplification efficiency was explored for serum microRNA-21 (miRNA-21) detection. …”
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Core–Shell Magnetic Gold Nanoparticles with Chitosan Coating as a SERS Substrate: A Rapid Detection Strategy for Malachite Green Contamination in Aquatic Foods by Yihui Yang, Tao Huang, Sijia Hu, Hang Ye, Jiali Xing, Shengnan Zhan

“…In this study, we developed a novel SERS-active magnetic substrate (MBs@CS@AuNPs) for detecting malachite green (MG) in aquatic products, including shrimp, cod, and aquaculture water. …”
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Multi-scale target intelligent detection method for coal, foreign object and early damage of conveyor belt surface under low illumination and dust fog by Hongwei FAN, Jinpeng LIU, Xiangang CAO, Chao ZHANG, Xuhui ZHANG, Man LI, Hongwei MA, Qinghua MAO

“…Finally, a lightweight and efficient channel attention mechanism is introduced into the backbone network and feature fusion network to improve channel utilization and early damage detection accuracy. …”
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Red Tide Detection Method Based on a Time Series Fusion Network Model: A Case Study of GOCI Data in the East China Sea by Tianhong Ding, Zhiqiang Xu, Yunjie Wang, Qinglian Hou, Xiangyong Liu, Fengshuang Ma

“…Experimental results demonstrate that CSF-RTDNet achieves robust detection of red tides with complex boundaries and continuous temporal patterns, attaining an accuracy of 95.89%, precision of 93.03%, recall of 96.34%, and a Kappa coefficient of 0.95. …”
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