WDFS-DETR: A Transformer-based framework with multi-scale attention for small object detection in UAV Engineering Tasks by Jinjiang Liu, Yonghua Xie

“…The framework integrates four custom-designed components to jointly enhance detection accuracy and efficiency. First, BasicBlock-WTCM (Wavelet-based Transform Coordinate Module) improves small object perception by modeling spatial and channel semantics across scales. …”
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Comparative analysis of data-driven models on detection and classification of electrical faults in transmission systems: Explainability, applicability and industrial implications by Chibueze D. Ukwuoma, Dongsheng Cai, Chiagoziem C. Ukwuoma, Chinedu I. Otuka, Qi Huang

“…Most data-driven fault detection methods often face challenges in accuracy, adaptability, and real-time implementation, particularly in complex transmission networks. …”
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Improved smart city security using a deep maxout network-based intrusion detection system with walrus optimization by Wahid Rajeh, Majed Aborokbah, Manimurugan S., Umar Albalawi, Ahamed Aljuhani, Osama Shibl Abdalghany Younes, Karthikeyan Periyasami

“…The DMN-WO model is ensured to be resource-efficient and suitable for real-time deployment on constrained devices like Raspberry Pi, typical in IoT systems. …”
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A CrossMod-Transformer deep learning framework for multi-modal pain detection through EDA and ECG fusion by Jaleh Farmani, Ghazal Bargshady, Stefanos Gkikas, Manolis Tsiknakis, Raul Fernandez Rojas

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Chronic lymphocytic leukemia (CLL) screening and abnormality detection based on multi-layer fluorescence imaging signal enhancement and compensation by Lemin Shi, Ping Gong, Mingye Li, Dianxin Song, Hao Zhang, Zhe Wang, Xin Feng

“…This study aims to enhance FISH signal clarity, improve screening efficiency, and reduce false negatives through an automated image acquisition and signal enhancement framework. …”
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An Optimization Method for PCB Surface Defect Detection Model Based on Measurement of Defect Characteristics and Backbone Network Feature Information by Huixiang Liu, Xin Zhao, Qiong Liu, Wenbai Chen

“…Printed Circuit Boards (PCBs) are essential components in electronic devices, making defect detection crucial. PCB surface defects are diverse, complex, low in feature resolution, and often resemble the background, leading to detection challenges. …”
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A Novel Spectrum Sensing Method for Multiple Unknown Signal Sources Using Frequency Domain Energy Detection and DBSCAN by Rui Gao, Guanghui Yan, Ruiting Niu, Wenwen Chang, Tianfeng Yan, Chunyang Tang

“…Multiple rounds of FDED detection are compiled into a two-dimensional signal detection matrix, which is subsequently analyzed by the DBSCAN algorithm to identify signal clusters. …”
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MHOE-DETR: A Ship Detection Method for Small and Fuzzy Targets Based on Satellite Remote Sensing Image Data by Zhuhua Hu, Xiyu Fan, Yaochi Zhao, Wei Wu, Jie Liu

“…This allows the proposed MHOE-DETR model to avoid thresholding and NMS), reducing the model’s computational complexity. The experimental results demonstrate that the MHOE-DETR algorithm, designed for this purpose, markedly enhances the detection performance of small and indistinct targets in private remote sensing datasets. …”
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Protective coatings for complex organic flexible materials I: characterization and tribological performance of TiO2 and ZnO films deposited by magnetron sputtering on cork by B. Tiss, D. Martínez-Martínez, C. Mansilla, J.R. Gomes, C.S. Abreu, N. Pereira, L. Cunha

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High-Precision defect detection and geometric verification in pipe jacking projects using computer vision and point cloud data by Haofeng Yan, Changyong Liu, Zhuliang Chen, Xincong Yang

“…Pipe jacking, a trenchless method for underground pipeline installation, minimizes surface disruption in urban environments but faces significant challenges in real-time quality control due to complex subsurface conditions. Existing approaches, primarily reliant on manual inspections or post-construction surveys, are labor-intensive, lack continuity, and often fail to detect defects or geometric deviations during construction. …”
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Development and validation of nanoplate-based RT-dPCR assay for canine respiratory coronavirus detection in various clinical samples by Panida Poonsin, Vorapun Wiwatvisawakorn, Chutchai Piewbang, Somporn Techangamsuwan

“…Abstract Background Canine respiratory coronavirus (CRCoV) is a major contributor to the canine infectious respiratory disease complex (CIRDC). Despite its widespread prevalence, molecular assays for CRCoV detection remain limited. …”
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MACA-Net: Mamba-Driven Adaptive Cross-Layer Attention Network for Multi-Behavior Recognition in Group-Housed Pigs by Zhixiong Zeng, Zaoming Wu, Runtao Xie, Kai Lin, Shenwen Tan, Xinyuan He, Yizhi Luo

“…Additionally, an Adaptive Multi-Path Attention (AMPA) mechanism integrates spatial-channel attention to enhance feature focus, ensuring robust performance in complex environments and low-light conditions. To further improve detection, a Cross-Layer Feature Pyramid Transformer (CFPT) neck employs non-upsampled feature fusion, mitigating semantic gap issues where small target features are overshadowed by large target features during feature transmission. …”
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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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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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Research on Calf Behavior Recognition Based on Improved Lightweight YOLOv8 in Farming Scenarios by Ze Yuan, Shuai Wang, Chunguang Wang, Zheying Zong, Chunhui Zhang, Lide Su, Zeyu Ban

“…In order to achieve accurate and efficient recognition of calf behavior in complex scenes such as cow overlapping, occlusion, and different light and occlusion levels, this experiment adopts the method of improving the YOLO v8 model to recognize calf behavior. …”
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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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OculusNet: Detection of retinal diseases using a tailored web-deployed neural network and saliency maps for explainable AI by Muhammad Umair, Jawad Ahmad, Oumaima Saidani, Mohammed S. Alshehri, Alanoud Al Mazroa, Muhammad Hanif, Rahmat Ullah, Muhammad Shahbaz Khan

“…This study introduces OculusNet, an efficient and explainable deep learning (DL) approach for detecting retinal diseases using OCT images. …”
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