Recent Advances in Microfluidic Impedance Detection: Principle, Design and Applications by Yigang Shen, Zhenxiao Wang, Tingyu Ren, Jianming Wen, Jianping Li, Tao Tang

“…This review systematically summarizes the core principles of microfluidic impedance detection technology, modeling methods for cell equivalent circuits, system optimization strategies, and recent research advancements in biological detection applications. …”
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Genderly: a data-centric gender bias detection system by Wael Khreich, Jad Doughman

“…We also curated new datasets as community resources for bias detection and mitigation. Our experiments used diverse preprocessing, feature engineering, and hyperparameter optimization methods for traditional ML models and large language models (LLMs) as gender bias detectors, comparing these results to evaluate model performance. …”
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Energy-Efficient Deep Learning for Cloud Detection Onboard Nanosatellite by Imane Khalil, Amina Daghouri, Mohammed Alae Chanoui, Zouhair Guennoun, Adnane Addaim

“…To address these challenges, we propose an optimized SegNet-based deep learning model implemented on the STM32H7 microcontroller for real-time cloud detection, designed to operate within the nanosatellite's strict energy budget. …”
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INTEGRATING CNN AND DICTIONARY MECHANISMS FOR EFFECTIVE LOOP CLOSURE DETECTION by Ayda Mohammed Sharif, Sadegh Abdollah Aminifar

“… Loop closure detection (LCD) remains a critical challenge in visual Simultaneous Localization and Mapping (SLAM), particularly in environments with repetitive structures or sparse textures where traditional methods suffer from perceptual aliasing and computational inefficiency. …”
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Research on SBMPC Algorithm for Path Planning of Rescue and Detection Robot by Lin-Lin Wang, Li-Xin Pan

“…The optimum solution of path planning is obtained from candidate solutions through continuous moving optimization of the defined cost function. The effects of the three sampling methods (viz., uniform sampling, Halton’s sampling, and CVT  sampling) on path planning performance are compared in simulations. …”
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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Abstract With the rapid development of the global financial market, the problem of financial fraud is becoming more and more serious, which brings huge economic losses to the market, consumers and investors and threatens the stability of the financial system. Traditional fraud detection methods based on rules and statistical analysis are difficult to deal with increasingly complex and evolving fraud methods, and there are problems such as poor adaptability and high false alarm rate. …”
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Research Progress in the Detection of Mycotoxins in Cereals and Their Products by Vibrational Spectroscopy by Jihong Deng, Mingxing Zhao, Hui Jiang

“…Researchers have explored various traditional detection methods to address this concern. However, as grain consumption becomes increasingly time-sensitive and dynamic, traditional approaches face growing limitations. …”
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Comparative Analysis of Audio Features for Unsupervised Speaker Change Detection by Alymzhan Toleu, Gulmira Tolegen, Rustam Mussabayev, Alexander Krassovitskiy, Bagashar Zhumazhanov

“…., influence speaker change detection (SCD) performance. The analysis is conducted using two unsupervised methods: Bayesian information criterion with Gaussian mixture model (BIC-GMM), a model-based approach, and Kullback-Leibler divergence with Gaussian Mixture Model (KL-GMM), a metric-based approach. …”
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Loss Adaptive Curriculum Learning for Ground-Based Cloud Detection by Tianhong Qi, Yanyan Hu, Juan Wang

“…While deep learning has advanced object detection through hierarchical feature learning and end-to-end optimization, conventional random sampling paradigms exhibit critical limitations in addressing hyperspectral ambiguity and low-distinguishability challenges in ground-based cloud detection. …”
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An Ensemble-Based Approach for Detecting Clickbait in Indonesian Online Media by Sandy Kurniawan, Adhe Setya Pramayoga, Yeva Fadhilah Ashari

“…These findings highlight the effectiveness of ensemble learning in enhancing clickbait detection performance and suggest potential for further optimization in model selection and integration strategies.…”
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Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…This Special Issue on “Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data” presents innovative strategies leveraging remote sensing technologies, artificial intelligence (AI), and non-destructive testing (NDT) to optimize road infrastructure assessment. …”
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Anomaly Detection for Aviation Cyber-Physical System: Opportunities and Challenges by Qurrat Ul Ain, Atif Aftab Ahmed Jilani, Nigar Azhar Butt, Shafiq Ur Rehman, Hisham Abdulrahman Alhulayyil

“…Anomaly detection in Aviation CPS is critical to ensuring safety and reliability. …”
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Inner Ear Multiple Primary Cell Type Detection System by Yu-Ting Li, Ching-Yun Chen, Bing-Siang Wang, Po-Hsuan Hung, Chia-Yu Lin

“…This paper proposes the Inner Ear Multiple Primary Cell Type Detection System (IEP-CDS), which addresses data limitations through IEP augmentation, overcomes detection errors in aggregated regions using preprocessing methods for training YOLO models, and achieves an F1-score greater than 20% compared to commercial software, completing counts in under one second. …”
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Leveraging multivariate information for community detection in functional brain networks by Maria Grazia Puxeddu, Maria Pope, Thomas F. Varley, Joshua Faskowitz, Olaf Sporns

“…We compared redundancy-dominated modules to those identified with conventional methods, uncovering a new organization of the transmodal cortex. …”
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Continuous Glucose Monitoring: A Transformative Approach to the Detection of Prediabetes by Liu X, Zhang J

“…CGM technology provides real-time, continuous data on glucose concentrations, surpassing the constraints of conventional monitoring methods. Both retrospectively analyzed and real-time CGM systems offer valuable tools for glycemic management, each with unique strengths. …”
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Deep learning algorithms for detecting fractured instruments in root canals by Ekin Deniz Çatmabacak, İrem Çetinkaya

“…The findings highlight the need for model-task alignment and optimization in medical imaging applications.…”
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Frobenius deep feature fusion architecture to detect diabetic retinopathy by C. Priyadharsini, Y. Asnath Victy Phamila

“…It can result in permanent vision impairment at advanced stages if not managed properly. Detecting various severity levels helps identify the level of treatment required for each patient, and directing them to the appropriate intensive care unit helps optimize the overall treatment efficacy. …”
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Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees by Cheng Shen, Yuewei Liu

“…Traditional defect detection methods predominantly rely on manual inspection, which suffers from low efficiency and high costs. …”
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SwinVision: Detecting Small Objects in Low-Light Environments by Tao Dai, Qi Wang, Yuancheng Shen, Shang Gao

“…Firstly, a Swin Transformer-based computing network is introduced and optimized for object detection in large-scale areas. …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…Abstract DETR (DEtection TRansformer) is a CV model for object detection that replaces traditional complex methods with a Transformer architecture, and has achieved significant improvement over previous methods, particularly in handling small and medium-sized objects. …”
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