Citrus Disease Detection Based on Dilated Reparam Feature Enhancement and Shared Parameter Head by Xu Guo, Xingmeng Wang, Wenhao Zhu, Simon X. Yang, Lepeng Song, Ping Li, Qinzheng Li

“…Current models struggle with accuracy and efficiency due to diverse leaf lesion patterns and complex orchard environments. …”
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Lane and Traffic Sign Detection for Autonomous Vehicles: Addressing Challenges on Indian Road Conditions by H. S. Gowri Yaamini, Swathi K J, Manohar N, Ajay Kumar G

“…Accurate and precise detection of lanes and traffic signs is predominant for the safety and efficiency of autonomous vehicles and these two significant tasks should be addressed to handle Indian traffic conditions. …”
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Research on a UAV-View Object-Detection Method Based on YOLOv7-Tiny by Yuyang Miao, Xihan Wang, Ning Zhang, Kai Wang, Lianhe Shao, Quanli Gao

“…In addition, introducing the Dilated Weighted Residual (DWR) attention module optimizes the information processing flow, enhancing the algorithm’s ability to capture key information, especially in complex backgrounds. These enhancements collectively enable the model to balance high detection accuracy and computational efficiency, making it well-suited for resource-constrained UAV platforms. …”
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Passion Fruit Disease Detection Using Sparse Parallel Attention Mechanism and Optical Sensing by Yajie He, Ningyi Zhang, Xinjin Ge, Siqi Li, Linfeng Yang, Minghao Kong, Yiping Guo, Chunli Lv

“…This study proposes a lightweight deep learning model incorporating a sparse parallel attention mechanism (SPAM) for passion fruit disease detection. Built upon a Convolutional Neural Network (CNN) backbone, the model integrates a dynamically selective attention mechanism to enhance detection performance in cases with complex backgrounds and multi-scale objects. …”
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Stochastic Fractal Search for Bayesian Network Structure Learning Under Soft/Hard Constraints by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…However, the acquisition of expert knowledge faces problems such as excessively high labor costs, limited expert experience, and the inability to solve large-scale and highly complex DAGs. Moreover, the current data learning methods also face the problems of low computational efficiency or decreased accuracy when dealing with large-scale and highly complex DAGs. …”
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Sowing, Monitoring, Detecting: A Possible Solution to Improve the Visibility of Cropmarks in Cultivated Fields by Filippo Materazzi

“…This study explores the integration of UAS-based multispectral remote sensing and targeted agricultural practises to improve cropmark detection in buried archaeological contexts. The research focuses on the Vignale plateau, part of the pre-Roman city of Falerii (Viterbo, Italy), where traditional remote sensing methods face challenges due to complex environmental and archaeological conditions. …”
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E-DoH: elegantly detecting the depths of open DoH service on the internet by Cong Dong, Jiahai Yang, Yun Li, Haoran Jiao, Chenglong Li, Xia Yin, Yuling Liu

“…Through experiments, our approach demonstrates a remarkable 80% improvement in time efficiency and only requires 4–20% traffic volume to complete the detection task. …”
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ASCDet: cross-space UAV object detection method guided by adaptive sparse convolution by Gui Cheng, Xubin Feng, Yan Tian, Meilin Xie, Chaoya Dang, Qing Ding, Zhenfeng Shao

“…UAV object detection, a critical aspect of remote sensing applications, faces challenges due to high object sparsity and complex backgrounds, leading to excessive computational demands. …”
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LN-DETR: cross-scale feature fusion and re-weighting for lung nodule detection by Dibin Zhou, Honggang Xu, Wenhao Liu, Fuchang Liu

“…However, challenges remain in deploying these methods in complex real-world scenarios. This paper introduces an enhanced lung nodule detection algorithm base on RT-DETR, called LN-DETR. …”
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YOLO-SSFA: A Lightweight Real-Time Infrared Detection Method for Small Targets by Yuchi Wang, Minghua Cao, Qing Yang, Yue Zhang, Zexuan Wang

“…Infrared small target detection is crucial for military surveillance and autonomous driving. …”
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Trade-off between toxicity and signal detection orchestrated by frequency- and density-dependent genes. by Laury Arthaud, Selim Ben Rokia-Mille, Hussein Raad, Aviv Dombrovsky, Nicolas Prevost, Maria Capovilla, Alain Robichon

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A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

“…However, existing deep learning models often face challenges in balancing detection accuracy and computational efficiency, especially for small objects in complex scenes. …”
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Hybrid Optimization Method for Social Internet of Things Service Provision Based on Community Detection by Bahar Allakaram Tawfeeq, Amir Masoud Rahmani, Abbas Koochari, Nima Jafari Navimipour

“…The average response time of IGBSA‐CD presents that it is efficient in all three tasks is 0.04 s. It also has a consistently lower response time, even when the task is complex. …”
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Traffic anomaly event detection and auxiliary decision-making based on large language models by LI Yanying, WANG Xinyu, WANG Xiao, SUN Changyin

“…The results show that compared with traditional methods, TMGPT significantly improves the accuracy of detection and reduced response time in the detection and assisted decision-making of abnormal traffic events, which demonstrates the application potential of large language models in complex urban traffic management.…”
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Research on the Forward Simulation and Intelligent Detection of Defects in Highways Using Ground-Penetrating Radar by Pengxiang Li, Mingzhou Bai, Xin Li, Chenyang Liu

“…Evaluation metrics such as precision, recall, F1-score, average precision (AP), and mean average precision (mAP) were used to assess the detection efficiency and accuracy for subgrade defect images. …”
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Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…This study explores technical methods based on light vision to address the problem of target detection and tracking by surface unmanned ships in complex environments. …”
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Passive indoor human daily behavior detection method based on channel state information by Xiaochao DANG, Yaning HUANG, Zhanjun HAO, Xiong SI

“…The daily behavior detection of indoor human based on CSI is developing rapidly in the field of WSN.At present,most of the research is still in the environment of 2.4 GHz,so the detection rate,robustness and overall performance still need to be improved.In order to solve this problem,a passive indoor human behavior detection method HDFi (Human Detection with Wi-Fi) based on CSI signal was proposed.The method was used to detect the indoor human daily behavior in a 5 GHz band environment,which was divided into three steps:data acquisition,data processing,feature extraction,online detection.Firstly,the experiment collected typical daily behavioral data in complex laboratory and relatively empty meeting room.Secondly,the amplitude and phase data with more obvious features were extracted and processed by low-pass filtering to obtain a set of stable and noise-free data,and then the fingerprint database was established effectively.Finally,in the real-time detection stage,the collected data features were classified by SVM algorithm to extract more stable eigenvalues,and a classification model of indoor human daily behavior detection was established,and then matched the data in the fingerprint database.The experimental results show that the proposed method has the characteristics of high efficiency,high precision and good robustness,and the method does not need any testing personnel to carry any electronic equipment,so it has high practicability.…”
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Aero-Engine Blade Defect Detection: A Systematic Review of Deep Learning Models by Yusra Abdulrahman, M. A. Mohammed Eltoum, Abdulla Ayyad, Brain Moyo, Yahya Zweiri

“…This is the first systematic review of deep learning models for aero-engine blade defect detection. The findings of this review demonstrate the potential of deep learning in detecting blade defects and improving the accuracy and efficiency of visual inspection. …”
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High catalytic nickel-platinum nanozyme enhancing colorimetric detection of Salmonella Typhimurium in milk by Jie Zhu, Lingyue Xu, Junlin Zhang, Yuxin Wang, Hongyue Yu, Chuanchuan Hao, Guohui Cheng, Daofeng Liu, Minghui Chen

“…Meanwhile, the antibody employed in this NiPt NP-based NLISA exhibits exceptional capture efficacy, generating a stable immune complex with Salmonella Typhimurium. The NiPt NP-based NLISA demonstrates sensitivity, specificity, convenience, and cost-efficiency for the detection of Salmonella Typhimurium. …”
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Enhancing Object Detection in Underground Mines: UCM-Net and Self-Supervised Pre-Training by Faguo Zhou, Junchao Zou, Rong Xue, Miao Yu, Xin Wang, Wenhui Xue, Shuyu Yao

“…However, limited computational resources and complex environmental conditions in mine shafts significantly impact the recognition and computational capabilities of detection models. …”
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