WeedSwin hierarchical vision transformer with SAM-2 for multi-stage weed detection and classification by Taminul Islam, Toqi Tahamid Sarker, Khaled R. Ahmed, Cristiana Bernardi Rankrape, Karla Gage

“…Our research evaluates several state-of-the-art object detection architectures, including DINO Transformer (with ResNet-101 and Swin backbones), Detection Transformer (DETR), EfficientNet B4, YOLO v8, and RetinaNet. …”
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Dual Improvements DCNv4 and AsDDet Mechanisms for Small Object Detection in Aerial Imagery by Fan Jiang, Hua-Ching Chen, Song-Lin Wei, Hsuan-Ming Feng

“…This study introduces a dual enhancement mechanism integrating Deformable Convolution v4 (DCNv4) and an Asymmetric Decoupled Detection Head (AsDDet) to significantly improve the detection performance of small objects in high-altitude unmanned aerial vehicle (UAV) imagery using YOLOv11 model architecture. …”
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Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

“…Balancing between model detection performance and efficiency poses many challenges. …”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…Although many countries have reduced or stopped large-scale testing measures, the detection of such diseases remains a propriety. Objective This study aims to develop a novel, lightweight deep neural network for efficient, accurate, and cost-effective detection of COVID-19 using a nasal breathing audio data collected via smartphones. …”
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YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping by Huijiao Yu, Xuehui Zhang, Jun Yan, Xianyong Meng

“…To address the issues of low efficiency and large errors in traditional manual cucumber fruit phenotyping methods, this paper proposes the application of keypoint detection technology for cucumber phenotyping and designs an improved lightweight model called YOLO11m-SCFPose. …”
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An MSRE-Assisted Glycerol-Enhanced RPA-CRISPR/Cas12a Method for Methylation Detection by Zhiquan Lu, Zilu Ye, Ping Li, Yike Jiang, Sanyang Han, Lan Ma

“…Conventional methylation detection methods relying on bisulfite conversion have limitations such as time-consuming, complex processes and sample degradation; thus, a more rapid and efficient method is needed. …”
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Star-YOLO: A Lightweight Real-Time Wheat Grain Detection Model for Embedded Deployment by Zhihang Qu, Xiao Liang, Sicheng Liang, Xiumei Guo

“…With the rapid advancement of precision agriculture, traditional object detection algorithms struggle with limited efficiency and accuracy in wheat grain detection and counting, while the need for real-time deployment of deep learning models on embedded devices becomes increasingly critical. …”
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EER-DETR: An Improved Method for Detecting Defects on the Surface of Solar Panels Based on RT-DETR by Jiajun Dun, Hai Yang, Shixin Yuan, Ying Tang

“…In the context of the rapid popularization of clean energy, the precise identification of surface defects on photovoltaic modules has become a core technical bottleneck limiting the operational efficiency of power stations. In response to the shortcomings of existing detection methods in identifying tiny defects and model efficiency, this study innovatively constructed the EER-DETR detection framework: firstly, a feature reconstruction module WDBB with a differentiable branch structure was introduced to significantly enhance the feature retention ability for fine cracks and other small targets; secondly, an adaptive feature pyramid network EHFPN was innovatively designed, which achieved efficient integration of multi-level features through a dynamic weight allocation mechanism, reducing the model complexity by 9.7% while maintaining detection accuracy, solving the industry problem of “precision—efficiency imbalance” in traditional feature pyramid networks; finally, an enhanced upsampling component was introduced to effectively address the problem of detail loss that occurs in traditional methods during image resolution enhancement. …”
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Intelligent single-cell manipulation: LLMs- and object detection-enhanced active-matrix digital microfluidics by Zhiqiang Jia, Chen Jiang, Jiahao Li, Yacine Belgaid, Mingfeng Ge, Li Li, Siyi Hu, Xing Huang, Tsung-Yi Ho, Wenfei Dong, Zhiwen Yu, Hanbin Ma

“…By combining this with a fully programmable lab-on-a-chip system, we present a breakthrough for SCSM by combining LLMs and object detection technologies. With the proposed platform, the single-cell sample generation rate and identification precision reach up to 25% and 98%, respectively, which are much higher than the existing platforms in terms of SCSM efficiency and performance. …”
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BCS_YOLO: Research on Corn Leaf Disease and Pest Detection Based on YOLOv11n by Shengnan Hao, Erjian Gao, Zhanlin Ji, Ivan Ganchev

“…Frequent corn leaf diseases and pests pose serious threats to agricultural production. Traditional manual detection methods suffer from significant limitations in both performance and efficiency. …”
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Detection of Stator Faults in Three-Phase Induction Motors Using Stray Flux and Machine Learning by Ailton O. Louzada, Wesley A. Souza, Avyner L. O. Vitor, Marcelo F. Castoldi, Alessandro Goedtel

“…Despite advancements in non-invasive sensing, challenges remain in balancing fault detection accuracy, computational efficiency, and adaptability to real-world conditions. …”
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Electrochemical detection of simple alkanes by utilizing a solid-state zirconia-based gas sensor by Anatoly S. Kalyakin, Alexander N. Volkov

“…While relatively simple gas mixtures (H2O+N2, O2+N2) have been successfully studied by means of ZrO2-based sensors, the precise detection of more complex compounds represents a challenging task. …”
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A Tactical Conflict Detection and Resolution Method for En Route Conflicts in Trajectory-Based Operations by Dong Sui, Kai Zhang

“…In the conflict detection (CD) submodule, a spatial data structure with low time complexity, the R tree algorithm, is used. …”
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Immobilization of DNA Aptamers on Polyester Cloth for Antigen Detection by Dot Blot Immunoenzymatic Assay (Aptablot) by Sally Smiley, Maria DeRosa, Burton Blais

“…A simple dot blot immunoenzymatic assay system was developed using polyester cloth coated with an oligo-DNA aptamer to provide a high-affinity macroporous surface for the efficient capture of a model protein analyte (thrombin) in complex sample matrices such as foods. …”
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A Triple-Channel Network for Maritime Radar Targets Detection Based on Multi-Modal Features by Kaiqi Wang, Zeyu Wang

“…Sea surface target detectors are often interfered by various complex sea surface factors such as sea clutter. Especially when the signal-to-clutter ratio (SCR) is low, it is difficult to achieve high-performance detection. …”
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Technical note: Flow cytometry assays for the detection, counting and cell sorting of polyphosphate-accumulating bacteria by C. Bouquet, H. Billard, H. Billard, C. C. Bidaud, J. Colombet, J. Colombet, Y.-T. Chang, J. Artigas, I. Batisson, K. Benzerara, F. Skouri-Panet, E. Duprat, A.-C. Lehours

“…The potential of flow cytometry to quantify and sort polyphosphate-accumulating bacteria in complex environmental samples, including soil, freshwater and sediments, was also examined. …”
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MA-YOLO: A Pest Target Detection Algorithm with Multi-Scale Fusion and Attention Mechanism by Yongzong Lu, Pengfei Liu, Chong Tan

“…To address the high computational complexity and inadequate feature representation in traditional convolutional networks, this study proposes MA-YOLO, an agricultural pest detection model based on multi-scale fusion and attention mechanisms. …”
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High resolution remote sensing image object detection algorithm based on improved YOLOv8 by ZHANG Xia, QIAO Huanyu, CAO Feng

“…In view of problems such as objects are interfered by complex background, objects are small and densely distributed, objects are multi-scale and their directions are random in high resolution remote sensing image data, an object detection algorithm for high resolution remote sensing image based on improved YOLOv8 was proposed. …”
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Feature Multi-Scale Enhancement and Adaptive Dynamic Fusion Network for Infrared Small Target Detection by Zenghui Xiong, Zhiqiang Sheng, Yao Mao

“…This study aims to address a series of challenges in infrared small target detection, particularly in complex backgrounds and high-noise environments. …”
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Quantifying solid volume of stacked eucalypt timber using detection-segmentation and diameter distribution models by Gianmarco Goycochea Casas, Zool Hilmi Ismail, Mathaus Messias Coimbra Limeira, Carlos Pedro Boechat Soares, José Marinaldo Gleriani, Daniel Henrique Brada Binoti, Carlos Alberto Araújo Júnior, Mohd Ibrahim Shapiai, Leonardo Ippolito Rodrigues, Tassius Menezes Araújo, Helio Garcia Leite

“…This procedure, which integrates automatic log detection with diameter distribution models, offers a scalable solution applicable to large and complex timber stacks. …”
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