Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…The proposed approach is efficient and feasible, offering a more stable and accurate disease detection system while utilizing fewer resources. This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques.…”
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Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

“…Moreover, we also propose a detection feature pyramid loss function to more accurately restore object features. …”
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DEM-based topographic change detection considering the spatial distribution of errors by Yufeng He, Shaohua Lei, Wen Dai, Xi Chen, Bo Wang, Yehua Sheng, Hui Lin

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Advances in the detection of virulence genes of Staphylococcus aureus originate from food by Yingying Zhao, Dandan Xia, Panpan Ma, Xiaofeng Gao, Wenyi Kang, Jinfeng Wei

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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

“…However, traditional methods of tire defect detection have encountered problems such as slow detection speed, complex tire defect backgrounds, and limited hardware resources. …”
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An investigation of the distribution of gaze estimation errors in head mounted gaze trackers using polynomial functions by Diako Mardanbegi, Andrew T. N. Kurauchi, Carlos H. Morimoto

“…In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions. Using simulated scenarios, we describe effects of four different sources of error: interpolation, extrapolation, parallax, and radial distortion. …”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. Through this pruning strategy, the model further reduces its dependence on computing resources while maintaining key performance. …”
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Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

“…In addition, the need for comprehensive train detection including pantograph-catenary systems and running gears, lead to an increased number of on-board devices, resulting in fewer computational resources available for each detection system, and complicating equipment installation and maintenance. …”
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Enhanced object detection in low-visibility haze conditions with YOLOv9s. by Yang Zhang, Bin Zhou, Xue Zhao, Xiaomeng Song

“…Furthermore, the implementation of a nonmonotonic strategy for dynamically adjusting the loss function weights significantly boosts the model's detection precision and training efficiency. …”
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A DFT insight into the potential of cycloparaphenylenes as efficient sensors for detecting Paracetamol by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…This study presents a computational investigation into the sensing capabilities of methylene-bridged [n]cycloparaphenylene ([n]MCPP, where n= 6, 8, and 10) nanorings for the detection of paracetamol using density functional theory (DFT) calculations. …”
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PA-YOLO-Based Multifault Defect Detection Algorithm for PV Panels by Wang Yin, Zhao Jingyong, Xie Gang, Zhao Zhicheng, Hu Xiao

“…For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. …”
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Study on lightweight strategies for L-YOLO algorithm in road object detection by Ji Hong, Kuntao Ye, Shubin Qiu

“…The demand for real-time, efficient object detection systems is growing. However, traditional algorithms often suffer from large parameter sizes and high computational costs, limiting their applicability in resource-constrained environments. …”
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Identification, functional analysis, and clinical applications of defective viral genomes by Xiaowei Yan, Yitong Pan, Peiying Li, Li Zhu, Jianhai Yu, Chenguang Shen, Bao Zhang, Wei Zhao

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Realizing depth measurement and edge detection based on a single metasurface by Yang Siwen, Wei Qunshuo, Zhao Ruizhe, Li Xin, Zhang Xue, Li Yao, Li Junjie, Jing Xiaoli, Li Xiaowei, Wang Yongtian, Huang Lingling

“…Double helix point source function is utilized, and three verification experiments are carried out, including double-helix beam calibration, 2D object and 3D object detection, respectively. …”
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Assessing the stability of indoor farming systems using data outlier detection by Jean Pompeo, Ziwen Yu, Chi Zhang, Songzi Wu, Ying Zhang, Celina Gomez, Melanie Correll

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Improving dependability with low power fault detection model for skinny-hash. by Sonal Arvind Barge, Gerardine Immaculate Mary

“…Two fault detection approaches are proposed to detect faults in cryptographic algorithms running on IoT devices. …”
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A review of deep learning models to detect malware in Android applications by Elliot Mbunge, Benhildah Muchemwa, John Batani, Nobuhle Mbuyisa

“…Smartphone applications use permissions to allow users to utilize different functionalities, making them susceptible to malicious software (malware). …”
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SWMD-YOLO: A Lightweight Model for Tomato Detection in Greenhouse Environments by Quan Wang, Ye Hua, Qiongdan Lou, Xi Kan

“…This study proposes SWMD-YOLO, a lightweight multi-scale detection network optimized for greenhouse scenarios. …”
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SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…These outcomes highlight the practicality and reliability of our method in detecting individuals overboard, contributing to more precise and resource-efficient solutions for real-time maritime rescue efforts.…”
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RipFinder: real-time rip current detection on mobile devices by Fahim Khan, Akila de Silva, Ashleigh Palinkas, Gregory Dusek, James Davis, Alex Pang

“…To address this, we propose a client-server ML model-based computer vision system designed specifically to improve rip current detection accuracy. This novel approach enables the app to function with or without internet connectivity, proving particularly beneficial in regions without lifeguards or internet access. …”
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