AG-Net3D: Embedding Attention Gate Into U-Net for 3D Seismic Data Fault Detection by Mingchun Chen, Hui Cao, Luofei Jia

“…Automatic fault detection of seismic data plays a remarkable role in ensuring the efficiency even effectiveness of oil and gas field exploration. …”
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Design of tomato picking robot detection and localization system based on deep learning neural networks algorithm of Yolov5 by Jianwei Zhao, Wei Bao, Leiyu Mo, Zhiting Li, Yushuo Liu, Jiaqing Du

“…Abstract In the context of modern agricultural intelligence, smart picking is becoming a crucial method for enhancing production efficiency. This paper proposes a tomato detection and localization system that integrates the YOLOv5 deep learning algorithm with the SGBM algorithm to improve detection accuracy and three-dimensional localization of tomatoes in complex environments. …”
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A Novel Dangerous Goods Detection Network Based on Multi-Layer Attention Mechanism in X-Ray Baggage Images by Xu Yang, Ting Lan, Yili Xu

“…This paper proposes a novel dangerous goods detection network (DGDN) designed to address the challenges of detecting dangerous goods in complex X-ray baggage images. …”
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Design Methodology of Power-Level Modulation for PV Power Loss Minimization and DC Series Arc Fault Detection and Extinguishing by Wan Kim, Hwa-Pyeong Park

“…Previous studies have proposed arc fault detection algorithms based on these input voltage drops. …”
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Incremental Pyraformer–Deep Canonical Correlation Analysis: A Novel Framework for Effective Fault Detection in Dynamic Nonlinear Processes by Yucheng Ding, Yingfeng Zhang, Jianfeng Huang, Shitong Peng

“…Smart manufacturing systems aim to enhance the efficiency, adaptability, and reliability of industrial operations through advanced data-driven approaches. …”
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WDFS-DETR: A Transformer-based framework with multi-scale attention for small object detection in UAV Engineering Tasks by Jinjiang Liu, Yonghua Xie

“…The model also generalizes well to UAVDT and DOTA datasets, demonstrating its applicability to real-world UAV-based detection tasks in complex engineering settings. Source code is available at: https://github.com/liuliuliu2002/WDFS-DETR.…”
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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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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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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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YOLOv5-MDS: Target Detection Model for PCB Defect Inspection Based on YOLOv5 Integrated With Mamba Architecture by Deming Guo, Qi Xi, Long Zhang, Jing Wang, Yilong Ye, Ziyi Zeng

“…Our proposed improvements enhance detection accuracy while maintaining computational efficiency. …”
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A Novel Convolutional Neural Network–Long Short-term Memory Model for Interplanetary Coronal Mass Ejection Detection by Junpei Li, Hong Chen, Jingjing Wang, Yanhong Chen, Bingxian Luo, Hao Deng

“…This study presents a convolutional neural network–long short-term memory (CNN-LSTM) model with dynamic loss function, designed to efficiently process complex multidimensional spatiotemporal data. …”
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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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Protocol-Agnostic and Packet-Based Intrusion Detection Using a Multi-Layer Deep-Learning Architecture at the Network Edge by Rodolphe Picot, Felipe Gohring de Magalhaes, Ahmad Shahnejat Bushehri, Maroua Ben Atti, Gabriela Nicolescu, Alejandro Quintero

“…Its protocol-agnostic design and customized preprocessing method enable it to efficiently detect network attacks across multiple protocols while preserving the original packet structure. …”
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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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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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Identifying All Matches of a Rigid Object in an Input Image Using Visible Triangles by Abdullah N. Arslan

“…It has been suggested that for objects identifiable by their corners, every triangle formed by these corner points can serve as a reference for detecting other corner points. This approach enables effective rigid object detection, including partial matches. …”
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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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