Bacterial network for precise plant stress detection and enhanced crop resilience by Shakeel Ahmed, Syed Muhammad Zaigham Abbas Naqvi, Muhammad Awais, Yongzhe Ren, Hao Zhang, Junfeng Wu, Linze Li, Vijaya Raghavan, Jiandong Hu

“…Simulations investigate the detection time for ABA, bacterial diffusion within plant roots, advection effects through shoots, and chemotaxis in response to attractant gradients in leaves. …”
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PS-YOLO: A Lighter and Faster Network for UAV Object Detection by Han Zhong, Yan Zhang, Zhiguang Shi, Yu Zhang, Liang Zhao

“…This increases the likelihood of false positives and missed detections, thereby complicating the detection process. …”
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Cardiovascular Disease Detection through Innovative Imbalanced Learning and AUC Optimization by Karthikeyan Palanisamy, Krishnaveni Krishnasamy, Praba Venkadasamy

“…This integration simplifies the model by reducing the number of parameters needing adjustment, making it particularly effective for handling imbalanced datasets through an efficient training process; 2) Theoretical analysis demonstrates that ImAUC-PSVM retains the same structural solution as standard PSVM. …”
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Gene fusion detection in long-read transcriptome sequencing data with GFvoter by Xiaolan Zhao, Zitong Ren, Junhai Qi, Enfeng Qi, Xiaoyu Zhao, Guojun Li, Ting Yu

“…GFvoter calls two RNA-seq aligners, two fusion detection tools, and a newly designed scoring mechanism to conduct the so-called voting process in turn, which enables the accurate detection of potential fusions. …”
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Immunosensor Enhanced with Silver Nanocrystals for On-Chip Prostate-Specific Antigen Detection by Timothy A. Okhai, Kefilwe V. Mokwebo, Marlon Oranzie, Usisipho Feleni, Lukas W. Snyman

“…Each stage of the fabrication process was characterized by cyclic voltammetry (CV). …”
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Artificial Intelligence-Based Skin Lesion Analysis and Skin Cancer Detection by Momina Qureshi, Muhammad Athar Javed Sethi, Sayed Shahid Hussain

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CONCEPTUAL APPROACHES TO THE RAPID DETECTION OF CAMPYLOBACTER SPP. IN MEAT OF SLAUGHTER ANIMALS by D. S. Bataeva, M. Yu. Minaev, Yu. K. Yushina, O. V. Sokolova, E. V. Zajko

“…However, Bolton’s enrichment medium is selective and, during the cultivation process, suppresses the growth of Gram-positive lactic acid bacteria. …”
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Study on Lightweight Bridge Crack Detection Algorithm Based on YOLO11 by Xuwei Dong, Jiashuo Yuan, Jinpeng Dai

“…Furthermore, a lightweight detection head (LDH) is introduced to process feature information from different channels using efficient grouped convolutions. …”
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Utilize Data Augmentation and Flexi Corner Block for Road Damage Detection by Zhaohui Wu, Runjing Zhao, Xingliang Sun, Zhaojia Li

“…This process typically involves detecting irregularities on the road surface, such as cracks and potholes, from images. …”
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Lightweight Pepper Disease Detection Based on Improved YOLOv8n by Yuzhu Wu, Junjie Huang, Siji Wang, Yujian Bao, Yizhe Wang, Jia Song, Wenwu Liu

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Multiobjective Optimization-Based Hyperspectral Unsupervised Band Selection for Anomaly Detection by Shihui Liu, Bing Xue, Meiping Song, Haimo Bao, Mengjie Zhang

“…First, the majority of multiobjective BS methods predominantly optimize accuracy in classification tasks, neglecting the emphasis on anomaly detection. Second, in the process of addressing the combinatorial optimization problem of multiobjective BS using evolutionary algorithms, insufficient consideration is given to the impact of bands on the recognition capability of an anomaly when devising solution strategies and determining optimal solutions. …”
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Detection of Seed Potato Sprouts Based on Improved YOLOv8 Algorithm by Yufei Li, Qinghe Zhao, Zifang Zhang, Jinlong Liu, Junlong Fang

“…A fast and efficient object recognition algorithm is required for the additional removal process to identify unqualified seed potatoes. In this paper, a lightweight deep learning algorithm, YOLOv8_EBG, is proposed to both improve the detection performance and reduce the model parameters. …”
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Early Detection of Autism Spectrum Disorder Through Automated Machine Learning by Khafsa Ehsan, Kashif Sultan, Abreen Fatima, Muhammad Sheraz, Teong Chee Chuah

“…This research proposes leveraging automated machine learning (AUTOML) to streamline the diagnostic process and enhance its accuracy. <b>Methods</b>: In this study, by collecting data from various rehabilitation centers across Pakistan, we applied a specific AUTOML tool known as Tree-based Pipeline Optimization Tool (TPOT) for ASD detection. …”
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Detection of distress in rural road pavements: an analysis of UAV altitude variations by L. Inzerillo, F. Acuto, A. Pisciotta, K. Mantalovas, G. Di Mino

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Detecting small seamounts in multibeam data using convolutional neural networks by Tobias Ziolkowski, Colin W. Devey, Agnes Koschmider

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High SERS performance of functionalized carbon dots in the detection of dye contaminants by Yanqiu Yang, Lingru Kong, Yong Ding, Lixin Xia, Shuo Cao, Peng Song

“…Methods: The enhanced substrate used for the detection of MG has been successfully constructed using PBA modulated Ag-CDs on a structured surface with rich binding sites. …”
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Using Trust and Reputation for Detecting Groups of Colluded Agents in Social Networks by Mariantonia Cotronei, Sofia Giuffre, Attilio Marciano, Domenico Rosaci, Giuseppe M. L. Sarne

“…We introduce an automatic procedure to provide EigenTrust with the necessary inputs, and we propose an appropriate algorithm that combines EigenTrust with a clustering process. This procedure groups agents based on their reputation scores to tackle the presence of different groups of colluded agents. …”
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Research on methods of working out seeding quantity of rice drill by ZHENG Yi-ping, HUA You-qing, LIN Jie, CHEM Li-neng

“…Consequently, a way is worked out to detect the seeding quantity during the non-singly seeding process.…”
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Lightweight and robust ship detection method driven by self-attention mechanism by Feng MA, Zihui SHI, Jie SUN, Chen CHEN, Xianbin MAO, Xinping YAN

“…To address this issue, a novel ship detection method called ShipDet is proposed which significantly improves performance through the design of a dedicated backbone network, improved feature extraction process, and constrained microscopic detection heads. …”
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Multichannel convolutional transformer for detecting mental disorders using electroancephalogrpahy records by Mamadou Dia, Ghazaleh Khodabandelou, Syed Muhammad Anwar, Alice Othmani

“…Before feeding the model as low-level features, the input is pre-processed using a common spatial pattern filter, a signal space projection filter, and a wavelet denoising filter. …”
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