SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…However, traditional intrusion detection methods exhibit several limitations, including insufficient feature extraction from network data, high model complexity, and data imbalance, which result in issues like low detection efficiency, as well as frequent false positives and missed alarms. …”
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Optimal Fuzzy Deep Neural Networks-Based Plant Disease Detection and Classification on UAV-Based Remote Sensed Data by M. Pajany, S. Venkatraman, U. Sakthi, M. Sujatha, Mohamad Khairi Ishak

“…The OFDNN-PDDC technique follows a three-stage process to enhance plant disease detection performance. At the primary level, the OFDNN-PDDC technique employs an improved ShuffleNetv2 model for learning complex and intrinsic feature patterns on the RS data. …”
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A Modified MobileNetv3 Coupled With Inverted Residual and Channel Attention Mechanisms for Detection of Tomato Leaf Diseases by Rubina Rashid, Waqar Aslam, Romana Aziz, Ghadah Aldehim

“…While deep learning models have been instrumental in detecting plant leaf diseases, they often involve complex models and significant computational demands to achieve optimal performance. …”
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Ghost-Attention-YOLOv8: Enhancing Rice Leaf Disease Detection with Lightweight Feature Extraction and Advanced Attention Mechanisms by Thanh Dang Bui, Tra My Do Le

“…In agricultural research, effective and efficient disease detection in crops is crucial for enhancing yield and sustainability. …”
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Improving Safety, Efficiency, Cost, and Satisfaction Across a Musculoskeletal Pathway Using the Digital Assessment Routing Tool for Triage: Quality Improvement Study by Cabella Lowe, Laura Atherton, Peter Lloyd, Anna Waters, Dylan Morrissey

“…Introduction of a new route to self-management for less complex conditions showed a cost reduction per patient of 73%, giving a saving of £1272.90 (US $1605.56) for 100 referrals. …”
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Optimized Error Detection and Correction in ATM Networks Using the Enhanced Berlekamp Massey Algorithm With Hybrid Automatic Repeat Request by Mahmut Aykac

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Rapid enrichment and SERS detection of fenitrothion and methyl parathion in vegetable and fruit juices using a dual-functionalized microneedle by Mengping Zhang, Hui Pan, Yafen Zeng, Xiao Meng, Wenwen Chen, Meng Jin, Hua Shao, Haiyan Wei, Cuijuan Wang

“…Fenitrothion and methyl parathion residues pose significant public health risks. Efficiently extracting and real-time detecting pesticide residues in complex matrices remains challenging. …”
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Advancing Particle Tracking: Self-Organizing Map Hyperparameter Study and Long Short-Term Memory-Based Outlier Detection by Max Klein, Niklas Dormagen, Lukas Wimmer, Markus H. Thoma, Mike Schwarz

“…Combined with automatic hyperparameter calibration, outlier detection and additional computational speed optimization, this work delivers a robust, versatile and efficient framework for PTV analysis.…”
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Application research on vector coherent frequency‐domain batch adaptive line enhancement in deep water by He Li, Tong Wang, Xinyi Guo, Lin Su, Yaxiao Mo

“…Abstract The low frequency line spectrum noise radiated by ships has strong stability and is difficult to eliminate, which is the key information required for passive signal detection. A vector coherent frequency‐domain batch adaptive line enhancement method is proposed to address the issue of insufficient detection capability of traditional scalar adaptive line enhancement (ALE) algorithms for ship characteristic line spectra in complex deep‐sea environments. …”
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A New Approach to Electrical Fault Detection in Urban Structures Using Dynamic Programming and Optimized Support Vector Machines by Reynaldo Villarreal, Sindy Chamorro-Solano, Yolanda Vega-Sampayo, Carlos Alejandro Espejo, Steffen Cantillo, Luis Gaviria, Jheifer Paez, Carlos Ochoa, Silvia Moreno, Claudet Polo, Roberto Pestana-Nobles, Camilo Montoya

“…Electrical power systems are crucial, yet vulnerable, due to their complex and interconnected nature, necessitating effective fault detection and diagnostics to ensure stability and prevent disruptions. …”
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Optimized small object detection in low resolution infrared images using super resolution and attention based feature fusion. by Weilun Wang, Jian Xu, Ruopeng Zhang

“…Infrared (IR) imaging is extensively applied in domains such as object detection, industrial monitoring, medical diagnostics, intelligent transportation due to its robustness in low-light, adverse weather, and complex environments. …”
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Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system by Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman

“…Hence, timely detection of these operational anomalies is crucial for optimizing performance and reducing maintenance costs. …”
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A novel YOLOv11-Driven deep learning algorithm for UAV multispectral oil spill detection in Inland lakes by Yu Zhang, Jian Xing, Weida Chen, Haitao Wang, Bingyu Shi, Yang Song, Xiaoou Huang, Zihan Jiang

“…Abstract Lake oil spills are challenging to detect accurately due to complex oil–water interactions resulting from water flow disturbances, vegetation occlusion, and the diffusion behavior of oil films. …”
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Synthesis of Rhodamine TEMPO Conjugates via Isonitrile‐Based Multicomponent‐Reactions for Mitochondria‐Targeted ROS‐Detection in Cancer Cells by Haider N. Sultani, Ibrahim M. Morgan, Hidayat Hussain, Haleh H. Haeri, Dariush Hinderberger, Goran N. Kaluđerović, Bernhard Westermann

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DGS-Yolov7-Tiny: a lightweight pest and disease target detection model suitable for edge computing environments by Ping Yu, Baoshu Zong, Xiaozhong Geng, Hui Yan, Baijin Liu, Cheng Chen, Hupeng Liu, Xiaoqing Xu

“…However, traditional object detection models are often computationally intensive and complex, rendering them unsuitable for real-time applications in edge computing. …”
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FD²-YOLO: A Frequency-Domain Dual-Stream Network Based on YOLO for Crack Detection by Junwen Zhu, Jinbao Sheng, Qian Cai

“…However, most existing methods use multi-scale and attention mechanisms to improve on a single backbone, and this single backbone network is often ineffective in detecting slender or variable cracks in complex scenarios. …”
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SD-YOLOv8: SAM-Assisted Dual-Branch YOLOv8 Model for Tea Bud Detection on Optical Images by Xintong Zhang, Dasheng Wu, Fengya Xu

“…This demonstrates its superior capability in efficiently detecting tea buds against complex backgrounds. …”
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Parameter Disentanglement for Diverse Representations by Jingxu Wang, Jingda Guo, Ruili Wang, Zhao Zhang, Liyong Fu, Qiaolin Ye

“…PDDR can be seamlessly integrated into modern networks, significantly improving the learning capacity of a network while maintaining the same complexity for inference. Experimental results show great improvements on various tasks, with an improvement of 1.47% over Residual Network 50 (ResNet50) on ImageNet, and we improve the detection results of Retina Residual Network 50 (Retina-ResNet50) by 1.7% Mean Average Precision (mAP). …”
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Enhanced Infrared Defect Detection for UAVs Using Wavelet-Based Image Processing and Channel Attention-Integrated SSD Model by Jining Zhao, RuiZhi Zhang, Shaogong Chen, Yanbo Duan, Zhiyuan Wang, Qingchen Li

“…We begin by constructing an infrared defect image processing model using wavelet multilayer decomposition, which effectively suppresses texture information within the complex background by reconstructing low-frequency and high-frequency coefficient images. …”
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A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…Abstract Deep neural networks are used to accurately detect, estimate, and predict human body poses in images or videos through deep learning-based human pose estimation. …”
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