An annotated Dataset and Benchmark for Detecting Floating Debris in Inland Waters by Guangchao Qiao, Mingxiang Yang, Hao Wang

“…However, complex light conditions in the water, small size objects and other factors pose a huge challenge for floating object detection. …”
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Advanced Nanoformulations for Detection and Removal of Poly- and Perfluoroalkyl Substances (PFAS) by Jyotish Kumar, Mahesh Narayan

“…The conventional, highly sensitive methods used for PFAS detection are LC-MS/MS and solid phase extraction, but they are very complex and expensive. …”
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Deep learning algorithms for detecting fractured instruments in root canals by Ekin Deniz Çatmabacak, İrem Çetinkaya

“…Conclusions DenseNet201’s superior performance highlights its clinical potential for FEI detection, while ResNet-18 offers a balance between accuracy and computational efficiency. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
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Robust Resilience Blocks Detection Problem in Dynamic Social Networks by Yuxin Gao, Jianming Zhu, Peikun Ni, Guoqing Wang

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Alzheimer’s Detection through 3D Convolutional Neural Networks by Ryan Hogan, Christoforos Christoforou

“…The benefits of our proposed 3D network are that it can assist in the exploration and detection of AD by mapping the complex heterogeneity of the brain, particularly in the limbic system and temporal lobe. …”
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Advancement of Fault Diagnosis and Detection Process in Industrial Machine Environment by Altaf S., Mehmood M. S., Soomro M. W.

“…Currently, manufacturing companies and researchers are making a great attempt to implement efficient fault diagnosis tools. The signal processing is a key step for the machine condition monitoring in complex industrial rotating electrical machines. …”
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Improving Threat Detection in Wazuh Using Machine Learning Techniques by Samir Achraf Chamkar, Mounia Zaydi, Yassine Maleh, Noreddine Gherabi

“…The increasing complexity and sophistication of cyber threats underscore the critical need for advanced threat detection mechanisms within Security Operations Centers (SOCs) to effectively mitigate risks and enhance cybersecurity resilience. …”
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Leveraging Deep Learning for Fault Detection and Localization in Distributed Systems by Debolina Ghosh, Jay Prakash Singh

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Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints by Lijuan Li, Siyi Wang, Jichao Ma, Xiaobing Gao

“…Focusing on the spatially constrained industrial environments and complex measurement specifications, the work reformulates Laser Radar inspection planning as a multi-constrained optimization problem challenge. …”
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Advances in Object Detection and Localization Techniques for Fruit Harvesting Robots by Xiaojie Shi, Shaowei Wang, Bo Zhang, Xinbing Ding, Peng Qi, Huixing Qu, Ning Li, Jie Wu, Huawei Yang

“…The accuracy of object detection and location is directly related to the picking efficiency, quality and speed of fruit-harvesting robots. …”
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Improved method for a pedestrian detection model based on YOLO by Yanfei LI, Chengyi DONG

“…The proposed method had superior performance in dense agricultural contexts while improving detection capabilities for pedestrian distribution patterns under complex farmland conditions, including variable lighting and mechanical occlusions. …”
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Ensemble Voting for Enhanced Robustness in DarkNet Traffic Detection by Varun Shinde, Kartik Singhal, Ahmad Almogren, Vineet Dhanawat, Vishal Karande, Ateeq Ur Rehman

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DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

“…Our objective is to construct an efficient deep learning model for peripheral blood cell analysis that achieves an optimized balance between inference speed, computational complexity, and detection accuracy. …”
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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…It focuses on evaluating deep learning techniques and unmanned aerial vehicles for crop disease detection. (Research purpose) The study aims to review and systemize scientific literature on the application of unmanned aerial vehicles, remote sensing technologies and deep learning 24 methods for the early detection and prediction of crop diseases. …”
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Machine Learning Detection of Melting Layers From Radar Observations by Yan Xie, Fraser King, Claire Pettersen, Mark Flanner

“…Compared to a traditional detection method, the U‐Net model increases the Probability of Detection by 57% and improves the mean Dice‐Sørensen coefficient from 0.69 to 0.91. …”
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A streamlined POCT solution for rapid infectious disease detection by Yaping Xie, Yan Yu, Shuaiwu Huang, Liangcheng Wan, Chang Wu, Chiwei Yin, Jianjun Li, Jiangang Ling, Lizhong Dai

“…Abstract Point-of-care testing (POCT) plays a crucial role in infectious disease screening due to its rapid detection and portability. However, current POCT systems face challenges such as lengthy sample preparation time, complex nucleic acid extraction, and limited real-time data transmission, extending patient waiting time. …”
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Explainable correlation-based anomaly detection for Industrial Control Systems by Ermiyas Birihanu, Imre Lendák

“…Anomaly detection is vital for enhancing the safety of Industrial Control Systems (ICS). …”
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Theoretical approaches to detecting anomalies in meter readings in scientific literature by D.V. Furikhata, T.A. Vakalyuk

“…Classification methods of supervised learning are analysed, which require pre-labelled data for model training but provide high accuracy in detecting known types of anomalies. The prospects for further development of anomaly detection technologies in the context of integrating IoT devices, technology development and implementing more complex deep learning algorithms are considered.…”
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Kneeliverse: A universal knee-detection library for performance curves by Mário Antunes, Tyler Estro, Pranav Bhandari, Anshul Gandhi, Geoff Kuenning, Yifei Liu, Carl Waldspurger, Avani Wildani, Erez Zadok

“…Additionally, Kneeliverse extends these algorithms to detect multiple knees and elbows in complex curves, employing a recursive approach. …”
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