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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Precision enhancement in wireless capsule endoscopy: a novel transformer-based approach for real-time video object detection by Tsedeke Temesgen Habe, Keijo Haataja, Pekka Toivanen

“…All three models demonstrated improved detection accuracy and computational efficiency compared to baseline methods.DiscussionThe RT-DETR framework significantly enhances precision and real-time performance in gastrointestinal abnormality detection using WCE. …”
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A Comparative Study of Machine Learning and Deep Learning Models for Automatic Parkinson’s Disease Detection from Electroencephalogram Signals by Sankhadip Bera, Zong Woo Geem, Young-Im Cho, Pawan Kumar Singh

“…Therefore, there is an urgent need for a more reliable and efficient technique for early detection of PD. Using the potential of electroencephalogram (EEG) signals, this study introduces an innovative method for the detection or classification of PD patients through machine learning, as well as a more accurate deep learning approach. …”
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Real-Time Smoke Detection in Surveillance Videos Using an Enhanced RT-DETR Framework with Triplet Attention and HS-FPN by Lanyan Yang, Yuanhang Cheng, Fang Xu, Boning Li, Xiaoxu Li

“…This study addresses the urgent need for an efficient and accurate smoke detection system to enhance safety measures in fire monitoring, industrial safety, and urban surveillance. …”
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Rapid and simple on-site salmonella detection in food via direct sample loading using a lipopolysaccharide-imprinted polymer by Solpa Lee, Hyunsoo Kim, Minwoo Kim, Ryun Kang, Inje Lim, Yongwoo Jang

“…Polydopamine (PDA) was used as the polymer matrix because of its cost-efficiency and functional versatility. The sensor demonstrated high sensitivity and selectivity, with a detection limit of 10 CFU/mL and a linear response over the 10²–10⁸ CFU/mL range. …”
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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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Electrochemical study of anti-platelets tirofiban HCl in dosage form using nanomaterials modified sensors: developed and green assessed by eco-scale and complex-GAPI approach by Mohamed. Rizk, Maha Mahmoud Abou El-Alamin, Ola Abd Elkhalek, Hassan A. M. Hendawy

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A Novel, Simple, and Reliable Spectrophotometric Determination of Total Hexavalent Chromium by Complexation with a New Reagent of Thiazole Linked to 2H-Chromen-2-One by Abdullah Akhdhar

“…The reaction of the TFZ ligand with Cr (VI) was optimized to produce a highly absorbent complex at 370 nm and pH 7.0 within 1 min. With a correlation coefficient of 0.9994, the linear concentration range ranges from 2 to 20,000 ng·mL−1. …”
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Criteria for Detecting Turn-To-Turn Short Circuit in Stator Windings Using Vector Analysis of Electric Motor Phase Currents by I. V. Zhezhelenko, V. E. Kryvonosov, S. V. Vasilenko

“…Turn circuits in the stator windings account for about 40 % of cases of damage to the insulation of the asynchronous motors windings. Untimely detection of the initial moment of the appearance of defects in the asynchronous motors or disruption of the operating modes of the supply network and current circuits result in emergency situations of the electrical complex, equipment downtime and damage. …”
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A Comprehensive Approach to Intrusion Detection in IoT Environments Using Hybrid Feature Selection and Multi-Stage Classification Techniques by G. Logeswari, J. Deepika Roselind, K. Tamilarasi, V. Nivethitha

“…The rapid expansion of Internet of Things (IoT) devices has led to an increasingly complex threat landscape, challenging traditional Intrusion Detection Systems (IDS) to effectively handle the vast and diverse data generated by IoT networks. …”
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RFCS-YOLO: Target Detection Algorithm in Adverse Weather Conditions via Receptive Field Enhancement and Cross-Scale Fusion by Gang Liu, Yingzheng Huang, Shuguang Yan, Enxiang Hou

“…It addresses challenges like complex backgrounds and problems of missing and mis-detecting traffic targets in bad weather. …”
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YOLO-SW: A Real-Time Weed Detection Model for Soybean Fields Using Swin Transformer and RT-DETR by Yizhou Shuai, Jingsha Shi, Yi Li, Shaohao Zhou, Lihua Zhang, Jiong Mu

“…The research stands out for its novel integration of three key advancements: the Swin Transformer backbone, which leverages local window self-attention to achieve linear O(N) computational complexity for efficient global context capture; the CARAFE dynamic upsampling operator, which enhances small target localization through context-aware kernel generation; and the RTDETR encoder, which enables end-to-end detection via IoU-aware query selection, eliminating the need for complex post-processing. …”
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Neurovision: A deep learning driven web application for brain tumour detection using weight-aware decision approach by Thota Rishik Sai Santhosh, Sachi Nandan Mohanty, Nihar Ranjan Pradhan, Tauseef Khan, Morched Derbali

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Regional classification and logistic regression modeling for surface freeze/thaw detection on the Qinghai-Tibet Plateau using CYGNSS data by Jiaxing He, Nanshan Zheng, Rui Ding, Xuexi Liu, Zhiyong Ma

“…To overcome these limitations, this study proposes an innovative approach that integrates the application of GNSS-R data with regional classification and logistic regression modeling, establishing an efficient framework for detecting surface F/T states. …”
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An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutatio... by Wuqiang Liu, Xiaoqiang Yang, Shen Jinxing

“…The health condition of rolling bearings, as a widely used part in rotating machineries, directly influences the working efficiency of the equipment. Consequently, timely detection and judgment of the current working status of the bearing is the key to improving productivity. …”
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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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QD-MLL-Based Single-Sideband Superchannel Generation Scheme With Kramers–Kronig Direct Detection Receivers by Mustafa Al-Qadi, Govind Vedala, Maurice O'Sullivan, Chongjin Xie, Rongqing Hui

“…For their capability of electronic dispersion compensation, transmission systems based on direct detection of single-sideband (SSB) signals are attractive candidates as energy-efficient and cost-effective alternative solutions to intradyne digital coherent systems for interdata center and metro applications. …”
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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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