Cross-modal interactive and global awareness fusion network for RGB-D salient object detection. by Runqing Li, Ling Yu, Zijian Jiang, Fanglin Niu

“…However, the existing RGB-D detection model still encounters difficulties in accurately recognising and highlighting salient objects when facing complex scenes containing multiple or small objects. …”
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A Lightweight Algorithm for Detection and Grading of Olive Ripeness Based on Improved YOLOv11n by Fengwu Zhu, Suyu Wang, Min Liu, Weijie Wang, Weizhi Feng

“…The proposed model exhibits significant advantages in terms of lightweight design and improved detection efficiency, demonstrating substantial potential for practical deployment. …”
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Evaluation of Intrusion Detection Systems in Cyber Security using Fuzzy OffLogic and MCDM Approach by Zhengrui Yang

“…In this study, thirteen widely used IDS models are assessed using a multi-criteria evaluation framework across four key dimensions: detection accuracy, resource efficiency, scalability, and false positive rate. …”
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FAMHE-Net: Multi-Scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection by Yixin Chen, Weilai Jiang, Yaonan Wang

“…These results highlight the effectiveness of FAMEH-Net in object detection within complex remote sensing images.…”
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YOLOv8-DEE: a high-precision model for printed circuit board defect detection by Feifan Yi, Ahmad Sufril Azlan Mohamed, Mohd Halim Mohd Noor, Fakhrozi Che Ani, Zol Effendi Zolkefli

“…Despite considerable efforts in PCB defect inspection, current detection models struggle with accuracy due to complex backgrounds and multi-scale characteristics of PCB defects. …”
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A Deep Learning Enabled Chest X-Ray Abnormality Detection Model for Radiology Assistance. by Ssempeebwa, Phillip, Ainembabazi, Patience

“…Therefore, there is a critical need for innovative solutions to improve the efficiency and accuracy of chest X-ray diagnosis. The main objective of this study is to develop and implement a Deep Learning-Enabled Chest X-ray Abnormality Detection model with automated report generation. …”
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Marine object detection in forward-looking sonar images via semantic-spatial feature enhancement by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Nan Xu

“…However, the challenges posed by seabed reverberation noise, complex marine environments, and varying object scales significantly hinder accurate detection of diverse object categories. …”
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Low-Complexity Vibration-Based Condition Monitoring for Rolling Bearings: A Novel Instantaneous Amplitude–Frequency Approach by Sulaiman Aburakhia, Ismail Hamieh, Sami Muhaidat, Abdallah Shami

“…Additionally, its moderate computational complexity makes the method well suited for real-time monitoring using smart transducers.…”
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Copper(I) Complexes with Terphenyl-Substituted NPN Ligands Bearing Pyridyl Groups: Synthesis, Characterization, and Catalytic Studies in the S-Arylation of Thiols by M. Trinidad Martín, Ana Gálvez del Postigo, Práxedes Sánchez, Eleuterio Álvarez, Celia Maya, M. Carmen Nicasio, Riccardo Peloso

“…These findings highlight the potential of well-defined Cu(I)–NPN complexes as efficient and versatile precatalysts for C–S bond formation.…”
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MSUD-YOLO: A Novel Multiscale Small Object Detection Model for UAV Aerial Images by Xiaofeng Zhao, Hui Zhang, Wenwen Zhang, Junyi Ma, Chenxiao Li, Yao Ding, Zhili Zhang

“…Due to the objects in UAV aerial images often presenting characteristics of multiple scales, small objects, complex backgrounds, etc., the performance of object detection using current models is not satisfactory. …”
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Nanoscale investigations of complex microbial interactions with terrestrial and extraterrestrial minerals using STEM based approach: implications for life on Earth and beyond by Tetyana Milojevic, Mihaela Albu, Ilse Letofsky-Papst, Artem Mashchenko

“…During these investigations, we have developed an efficient combined approach of microbiology, wet chemistry and STEM based spectroscopy nanoanalysis. …”
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Efficiently Modeling Lateral Vehicle Movement Including its Temporal Interrelations Using a Two-Level Stochastic Model by N. Neis, J. Beyerer

“…It is shown that the model allows for efficient calibration, is able to replicate the behavior of these drivers, and is characterized by short runtimes. …”
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Advanced fault detection methodologies and communication protocols for DC micro grid -A technical review by Athira Earath Shivadasan, Prabhakar Karthikeyan Shanmugam

“…This critical study provides valuable information for researchers and professionals aiming to refine fault detection and isolation methods and improve the efficiency of DC microgrid systems.…”
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Rapid and Efficient Screening of <i>Helicobacter pylori</i> in Gastric Samples Stained with Warthin–Starry Using Deep Learning by José Aneiros-Fernández, Pedro Montero Pavón, Natalia García Gómez, Rosa María Palo Prian, Ismael Sánchez García, Ana Isabel Romero Ortiz, Rodrigo López Castro, César Casado-Sánchez, Víctor Sánchez Turrión, Antonio Luna, Manuel Álvaro Berbís

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A software reliability model for open source big data system considering fault introduction and fault removal efficiency by Jinyong Wang, Haijun Geng, Pengda Li

“…In this paper, we focus on the characteristics of open source big data system software development and testing, such as the complexity of fault detection, the possibility of introducing new faults and fault removal efficiency factors during fault debugging, to establish a new software reliability model. …”
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Development and validation of mPCR-CEFA for detecting multiple deletion and non-deletion thalassemia genotypes by Jingping Xu, Jingping Xu, Baoyan Ren, Qixun Fang, Kangfeng Lin, Kangfeng Lin, Xingan Xing, Xingan Xing, Jingting Lin

“…The method demonstrated a high accuracy rate of 99.5%. It successfully detected complex compound genotypes like αCD 74α/−α4.2, βCD 17/βN and αWSα/--SEA, βCD 37/βN (or αWSα/--SEA, βCD 37/βCD 37), which were challenging for traditional approaches.ConclusionThe mPCR-CEFA method is a reliable, efficient, and scalable tool for genetic diagnosis of thalassemia. …”
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LiDAR-based Road Intrusion Detection Technology forAutonomous-rail Rapid Tram by LONG Teng, LIU Sisi, HU Yunqing, LI Xiaoguang, YUAN Xiwen, PAN Wenbo, LUO Yiping, YU Wentian

“…In order to ensure the operation safety of autonomous-rail rapid tram and improve the efficiency and robustness of road intrusion detection, a road intrusion detection technology based on multi-LiDAR was proposed in this paper. …”
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A novel machine learning model for perimeter intrusion detection using intrusion image dataset. by Shahneela Pitafi, Toni Anwar, I Dewa Made Widia, Zubair Sharif, Boonsit Yimwadsana

“…When handling high-dimensional data, the existing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm faces efficiency issues due to its complexity and varying densities. …”
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An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network by Yanbin Weng, Meng Xu, Xiahu Chen, Cheng Peng, Hui Xiang, Peixin Xie, Hua Yin

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Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles by Naif Almakayeel

“…Machine learning (ML) techniques cannot detect every new and complex malware variant. The deep learning (DL) model is an efficient tool for detecting various malware variants. …”
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