PD-YOLO: a novel weed detection method based on multi-scale feature fusion by Shengzhou Li, Zihan Chen, Jialong Xie, Hewei Zhang, Jianwen Guo

“…This research not only presents an efficient and accurate weed detection method but also offers new insights and technological advances for automated weed detection in agriculture.…”
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Partition detection for large scale ad hoc networks by LI Jian-dong, TIAN Ye, SHENG Min, ZHANG Yan, YAO Jun-liang

“…As the failure of a critical node will directly partition a network,a theorem for critical node identification was proved,which indicates that node degree Ni and elementary loop degree Mi of node i are two decisive factors for the exis-tence of a critical node and shows that Ni-Mi≥ 2 is the necessary and sufficient condition for node i being critical.Based on the theorem,a distributed topology partition detection algorithm（distributed partition detection protocol,DPDP） was presented for large scale networks,which achieves the goal of partition detection efficiently by detecting critical nodes in a local area.Theoretic analysis and experiment results show that DPDP has the advantages of low complexity,high accuracy,low cost as well as good scalability,and is superior to other algorithms.…”
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Hybrid metaheuristic optimization for detecting and diagnosing noncommunicable diseases by Saleem Malik, S. Gopal Krishna Patro, Chandrakanta Mahanty, Saravanapriya Kumar, Ayodele Lasisi, Quadri Noorulhasan Naveed, Anjanabhargavi Kulkarni, Abdulrajak Buradi, Addisu Frinjo Emma, Naoufel Kraiem

“…Abstract In our data-driven world, the healthcare sector faces significant challenges in the early detection and management of Non-Communicable Diseases (NCDs). …”
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Research Advances in Underground Bamboo Shoot Detection Methods by Wen Li, Qiong Shao, Fan Guo, Fangyuan Bian, Huimin Yang

“…Underground winter bamboo shoots, prized for their high nutritional value and economic significance, face harvesting challenges owing to inefficient manual methods and the lack of specialized detection technologies. This review systematically evaluates current detection approaches, including manual harvesting, microwave detection, resistivity methods, and biomimetic techniques. …”
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Cross-Hole Computed Tomography in Geological Investigation of Shenzhen Metro Complex Karst Section by ZHANG Jiwei, HE Jiankai, REN Aobo, QU Chaolei, WANG Yajie

“…［Result & Conclusion］ The electromagnetic wave CT method is not as precise as the elastic wave CT method in depicting the rock surface, but the electromagnetic wave CT method has advantages in terms of long detection hole distance. The working efficiency of elastic wave CT method is higher than that of the electromagnetic wave CT method. …”
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Fault Detection of the Power System Based on the Chaotic Neural Network and Wavelet Transform by Zuoxun Wang, Liqiang Xu

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Multisensor-Weighted Fusion Algorithm Based on Improved AHP for Aircraft Fire Detection by Rui Wang, Yahui Li, Hui Sun, Kaixin Yang

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Ion-Pair Complex of Trimethoprim with Alizarin Yellow and its Determination and Extraction by LLE and DLLME by Araf I. Jabbar, Mohammed Z. Thani, Ali I. Khaleel

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βTrCP facilitates MRN complex localization on chromatin to enhance DNA repair by Alejandro Belmonte-Fernández, Joaquín Herrero-Ruíz, Carmen Sáez, Miguel Á. Japón, Mar Mora-Santos, Francisco Romero

“…Upon detecting DNA breaks, this complex triggers a cascade of signaling events that regulate both cell cycle arrest and DNA repair. …”
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Analysis of Algorithms for Detecting Users’ Behavioral Models based on Sessions Data by Vitaly Zabiniako, Toms Rožkalns, Erika Nazaruka, Jurijs Kornienko

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Integrating Proteomics and GWAS to Identify Key Tissues and Genes Underlying Human Complex Diseases by Chao Xue, Miao Zhou

“…Background: The tissues of origin and molecular mechanisms underlying human complex diseases remain incompletely understood. Previous studies have leveraged transcriptomic data to interpret genome-wide association studies (GWASs) for identifying disease-relevant tissues and fine-mapping causal genes. …”
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AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features by Ruochen Zhang, Hyeung-Sik Choi, Dongwook Jung, Phan Huy Nam Anh, Sang-Ki Jeong, Zihao Zhu

“…To overcome these limitations, we propose AuxDepthNet, an efficient framework for real-time monocular 3D object detection that eliminates the reliance on external depth maps or pre-trained depth models. …”
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A Novel YOLO Algorithm Integrating Attention Mechanisms and Fuzzy Information for Pavement Crack Detection by Qingqing Li, Tianshu Wu, Tingfa Xu, Jianmei Lei, Jiu Liu

“…In response, automated crack detection systems based on deep learning have emerged, offering more efficient and accurate solutions. …”
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An Electrochemical Sensor for the Simultaneous Detection of Pb²⁺ and Cd²⁺ in Contaminated Seawater Based on Intelligent Mobile Detection Devices by Zizi Zhao, Wei Qu, Chengjun Qiu, Yuan Zhuang, Kaixuan Chen, Yi Qu, Huili Hao, Wenhao Wang, Haozheng Liu, Jiahua Su

“…Traditional methods for detecting marine Pb²⁺ and Cd²⁺ rely on laboratory analyses, which are hindered by limitations such as sample degradation during transport and complex operational procedures. …”
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Improving Object Detection in High-Altitude Infrared Thermal Images Using Magnitude-Based Pruning and Non-Maximum Suppression by Yajnaseni Dash, Vinayak Gupta, Ajith Abraham, Swati Chandna

“…We converted dataset annotations from the COCO and PASCAL VOC formats to YOLO’s required format, enabling efficient model training and inference. The results demonstrate the proposed architecture’s superior speed and accuracy, effectively handling thermal signatures and object detection. …”
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Efficient hardware error correction with hybrid on-offline configuration algorithm for optical processor by Zichao Zhao, Huihui Zhu, Qishen Liang, Haoran Ma, Ziyi Fu, Xingyi Jiang, Bei Chen, Yuehai Wang, Tian Chen, Yuzhi Shi, Jianyi Yang

“…This innovative approach combines offline initial value presetting with online perturbed optimization iteration algorithm, enabling precise and highly efficient error correction. We benchmark the algorithm’s performance in complex-valued matrix configuration and classification tasks, demonstrating robust error correction capabilities, including high reconstruction fidelity (≥98%), rapid convergence (≤10 iterations), and reduced dependence on detection devices. …”
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Data-Efficient Bone Segmentation Using Feature Pyramid- Based SegFormer by Naohiro Masuda, Keiko Ono, Daisuke Tawara, Yusuke Matsuura, Kentaro Sakabe

“…While Convolutional Neural Networks (CNNs) are commonly used for segmentation, they often struggle with complex shapes due to their focus on texture features and limited ability to incorporate positional information. …”
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Insights into the Silver Camphorimine Complexes Interactions with DNA Based on Cyclic Voltammetry and Docking Studies by Joana P. Costa, Gonçalo C. Justino, Fernanda Marques, M. Fernanda N. N. Carvalho

“…The formation of a light grey product adherent to the Pt electrode in the case of {Ag(OH)} and {Ag₂(µ-O)} complexes further corroborates the interaction of the complexes with CT-DNA detected by CV. …”
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Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes by Weijin JIANG, Ying YANG, Tiantian LUO, Wenying ZHOU, En LI, Xiaowei ZHANG

“…Mining key nodes in the network plays a great role in the evolution of information dissemination, virus marketing, and public opinion control, etc.The identification of key nodes can effectively help to control network attacks, detect financial risks, suppress the spread of viruses diseases and rumors, and prevent terrorist attacks.In order to break through the limitations of existing node influence assessment methods with high algorithmic complexity and low accuracy, as well as one-sided perspective of assessing the intrinsic action mechanism of evaluation metrics, a comprehensive influence (CI) assessment algorithm for identifying critical nodes was proposed, which simultaneously processes the local and global topology of the network to perform node importance.The global attributes in the algorithm consider the information entropy of neighboring nodes and the shortest distance nodes between nodes to represent the local attributes of nodes, and the weight ratio of global and local attributes was adjusted by a parameter.By using the SIR (susceptible infected recovered) model and Kendall correlation coefficient as evaluation criteria, experimental analysis on real-world networks of different scales shows that the proposed method is superior to some well-known heuristic algorithms such as betweenness centrality (BC), closeness centrality (CC), gravity index centrality(GIC), and global structure model (GSM), and has better ranking monotonicity, more stable metric results, more adaptable to network topologies, and is applicable to most of the real networks with different structure of real networks.…”
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Assessing data and sample complexity in unmanned aerial vehicle imagery for agricultural pattern classification by Linara Arslanova, Sören Hese, Marcel Fölsch, Friedemann Scheibler, Christiane Schmullius

“…The study also proposes a customized set of input layers for each crop type and identifies minimum patch sizes to enhance the efficiency of detecting specific agricultural patterns. …”
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