Efficient fault diagnosis in rolling bearings lightweight hybrid model by Peng Yang, Bozheng Zhang, Jianda Zhao

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Low-Complexity Ultrasonic Flowmeter Signal Processor Using Peak Detector-Based Envelope Detection by Myeong-Geon Yu, Dong-Sun Kim

“…In these environments, a low-power design is critical to maximize energy efficiency. Real-time data collection and remote consumption monitoring through remote metering significantly enhance network flexibility and efficiency. …”
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SkinEHDLF a hybrid deep learning approach for accurate skin cancer classification in complex systems by Umesh Kumar Lilhore, Yogesh Kumar Sharma, Sarita Simaiya, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi

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Using lightweight method to detect landslide from satellite imagery by Jinchi Dai, Xiaoai Dai, Renyuan Zhang, JiaXin Ma, Wenyu Li, Heng Lu, Weile Li, Shuneng Liang, Tangrui Dai, Yunfeng Shan, Donghui Zhang, Lei Zhao

“…Increasingly general-purpose detection models are being deployed for these complex and dynamic tasks involving features that are difficult to characterize. …”
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The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat by Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, Md. Nurealam Siddiqui, Mohammad Kamruzzaman, Ahossi Patrice Koua, Jens Léon

“…ABSTRACT Currently in wheat breeding, genome wide association studies (GWAS) have successfully revealed the genetic basis of complex traits such as nitrogen use efficiency (NUE) and its biological processes. …”
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Trends in the Development of Oil and Gas Complex by A. P. Garnov, V. Yu. Garnova, N. P. Tishkina

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Ultra-lightweight tomatoes disease recognition method based on efficient attention mechanism in complex environment by Wenbin Sun, Zhilong Xu, Kang Xu, Lin Ru, Ranbing Yang, Rong Wang, Jiejie Xing

“…To minimize hardware resource consumption, we developed five inverted residual modules coupled with an efficient attention mechanism, resulting in an ultra-lightweight recognition model that effectively balances model complexity and accuracy. …”
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Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis by Ben Gabrielson, Hanlu Yang, Trung Vu, Vince Calhoun, Tulay Adali

“…In this paper, we introduce an efficient subset-based form of the Tucker decomposition, by selecting coresets from the tensor modes such that the resulting core tensor can well-approximate the full tensor. …”
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Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

“…Feature selection is crucial in machine learning and data mining, significantly impacting model performance and efficiency by reducing dimensionality, mitigating overfitting, and improving interpretability. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…However, it suffers from low accuracy (in NLOS traffic), noise, and multipath fading issues. In large complex spaces, such as museums, where heavy visitor traffic is expected to seriously impact the ability to maintain LOS, RSSI coupled with Bluetooth Low Energy (BLE) seems ideal in terms of market availability, cost-/energy-efficiency and scalability that affect competing technologies, provided it achieves adequate accuracy. …”
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MEIS-YOLO: Improving YOLOv11 for efficient aerial object detection with lightweight design by Yicheng Liu, Jinsong Wu, Li Chen

“…The core innovation of the model lies in the introduction of a Multi-scale Edge Information Selection (MEIS) module, which selects key features highly relevant to the target detection task from multi-scale features, strengthening the representation of edge information and significantly improving detection performance under conditions of small targets and complex backgrounds. …”
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Evaluating YOLO Models for Efficient Crack Detection in Concrete Structures Using Transfer Learning by Muhammad Sohaib, Muzamal Arif, Jong-Myon Kim

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A secure and efficient deep learning-based intrusion detection framework for the internet of vehicles by Hasim Khan, Ghanshyam G. Tejani, Rayed AlGhamdi, Sultan Alasmari, Naveen Kumar Sharma, Sunil Kumar Sharma

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An EfficientNetv2-based method for coal conveyor belt foreign object detection by Tao Hu, Deyu Zhuang, Jinbo Qiu

“…This article proposes a foreign object detection method for coal conveyor belts based on EfficientNetv2. …”
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ResM-FusionNet for efficient landslide detection algorithm with a hybrid architecture by Xuqing Ren, Xu Wu, Donghao Zhai, Xiangpeng Wang, Ningbo He, Mehreen Tarif

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HiViT-IDS: An Efficient Network Intrusion Detection Method Based on Vision Transformer by Hai Zhou, Haojie Zou, Wei Li, Di Li, Yinchun Kuang

“…To balance high detection accuracy with reduced time consumption, this study introduces an efficient intrusion detection approach based on the Vision Transformer (ViT), utilizing its powerful feature extraction capabilities to enhance performance. …”
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Multi‐scale feature extraction for energy‐efficient object detection in remote sensing images by Di Wu, Hongning Liu, Jiawei Xu, Fei Xie

“…Deep learning methods, especially one‐stage detectors, for example, the Real‐Time Object Detector (RTMDet) offers advanced solutions with efficient network architectures. Nevertheless, difficulty in feature extraction from complex backgrounds and target localisation in scale variations images limits detection accuracy. …”
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AG-Yolo: Attention-Guided Yolo for Efficient Remote Sensing Oriented Object Detection by Xiaofeng Wang, Chengshan Han, Liang Huang, Ting Nie, Xin Liu, Hao Liu, Mingxuan Li

“…But complex backgrounds in remote sensing images severely degrade detection performance. …”
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An Efficient License Plate Detection Approach Using Lightweight Deep Convolutional Neural Networks by Hoanh Nguyen

“…This paper proposes an efficient license plate detection method based on lightweight deep convolutional neural networks for improving the detection speed. …”
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EADetection: An efficient and accurate sequential behavior anomaly detection approach over data streams by Li Cheng, Yijie Wang, Yong Zhou, Xingkong Ma

“…Due to the increasing arriving rate and complex relationship of behavior data streams, how to detect sequential behavior anomaly in an efficient and accurate manner has become an emerging challenge. …”
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