Wavelet-Attention Swin for Automatic Diabetic Retinopathy Classification by Rasha Ali Dihin, Ebtesam N. AlShemmary, Waleed A. M. Al-Jawher

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Accuracy and precision of fixation locations recorded with the low-cost Eye Tribe tracker in different experimental set-ups by Kristien Ooms, Lien Dupont, Lieselot Lapon, Stanislav Popelka

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A comprehensive Malabar Spinach dataset for diseases classificationMendeley Data by Mushfiqur Rahman, Md Al Mamun

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The Biological Diversity of Fruit Flies (Diptera: Drosophilidae) in Russia: A Description of a Set of Own and Published Data and a Complete List of Species by Nikolai G. Gornostaev, Alexander B. Ruchin, Mikhail N. Esin, Evgeniy A. Lobachev, Irina G. Esina

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Advances in machine learning for the detection and characterization of microplastics in the environment by M. Maksuda Khanam, M. Khabir Uddin, Julhash U. Kazi

“…Extending these capabilities further, hyperspectral imaging combines spatial and spectral data to generate comprehensive chemical maps, enabling the simultaneous assessment of polymer composition and distribution. …”
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Bearing Velocity Determination with Lifting Wheel Set Detectionfor HXD3C Locomotive by ZENG You-heng, CHEN Xi, LIU Shi-yong

“…Aim to the quality problems of HXD3C locomotive, characteristic of HXD3C locomotive wheel set driving control wasdiscussed, and the key factor that lifting wheel set detection could not determine bearing velocity was pointed out. …”
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A Data-Driven Approach to Mitigate Evolving Volumetric Attacks in Programmable Networks by Muhammad Saqib, Halima Elbiaze, Roch H. Glitho

“…The proposed method sets drift detection thresholds based on baseline performance from historical (i.e., training) data and uses these thresholds to detect anomalies in unseen (i.e., testing) data. …”
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Chemical Nose-Based Non-Invasive Detection of Breast Cancer Using Exhaled Breath by Yosef Matana, Shai Libson, Barak Amihood, Zvi Boger, David Lieberman, Offer Zeiri, Yehuda Zeiri

“…An SVM model was then optimized with respect to the accuracy matrix using a validation set by applying a Monte Carlo cross-validation with 100 iterations, with each iteration containing 20% of the data. …”
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Anomaly detection of industrial state quantity time-Series data based on correlation and long short-term memory by Mingxin Tang, Wei Chen, Wen Yang

“…Anomaly detection of multi-dimensional time-series data is a key research area, and the analysis of control, switching, and other state signals (i.e., industrial state quantity time series) is of particular importance to the operational sciences. …”
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Advanced Anomaly Detection in Smart Grids Using Graph Convolutional Networks With Integrated Node and Line Sensor Data by Mahdi Zarif, Ramin Moghaddass

“…The proposed method, which was evaluated on the IEEE 118-bus system and a set of simulated data, demonstrated outstanding performance in handling complex topologies and missing data. …”
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Comparison of machine learning and validation methods for high-dimensional accelerometer data to detect foot lesions in dairy cattle. by Muhammad Usman Riaz, Luke O'Grady, Conor G McAloon, Finnian Logan, Isobel Claire Gormley

“…Using data containing 20 thousand recordings from 383 dairy cows in 11 dairy herds, this study evaluated the effectiveness of ML methods in detecting foot lesions in dairy cows using accelerometer data, with a focus on dimensionality reduction approaches and cross-validation strategies. …”
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Improving Presentation Attack Detection Classification Accuracy: Novel Approaches Incorporating Facial Expressions, Backdrops, and Data Augmentation by Tayyaba Riaz, Adeel Anjum, Madiha Haider Syed, Semeen Rehman

“…The student network, specifically focusing on the nuanced detection of genuine samples in target domains, leverages minimalist yet representative attack data. …”
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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

“…Trained on data from 1998 January 1 to 2009 December 31, 189 out of 230 ICMEs are detected in the test set, achieving an F1 score of 81.29%.…”
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Waterbody Detection and Reservoir Water Level Prediction Using Bayesian Mixture Models with Sentinel-1 GRD Data by DongHyeon Yoon, Ha-Eun Yu, Euiho Hwang, Ki-mook Kang, Gibeom Nam, Jin-Gyeom Kim

“…For future research, higher-resolution data or complementary algorithms may further enhance detection accuracy for smaller and more complex water features, contributing to more refined water resource management strategies.…”
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Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras by Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedito, Fernando Mateo, Antonio J. Serrano-López

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A Novel Framework for Financial Cybersecurity and Fraud Detection Using XAI-RNN-SGRU by Smarajit Ghosh

“…Traditional network security methods need more scalability, data protection, and difficulty detecting advanced threats. …”
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YOLO-Based Real-Time Detection of Power Line Poles from Unmanned Aerial Vehicle Inspection Vision by Jingdong GUO, Bin CHEN, Renshu WANG, Jiayu WANG, Linlin ZHONG

“…In this paper a real-time detection model based on YOLO deep learning algorithm is presented to detect the status of power line poles automatically from the UAV vision data after disaster. …”
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Integrating an LFA Carbapenemase Detection System into the Laboratory Diagnostic Routine: Preliminary Data and Effectiveness Against Enzyme Variants by Maddalena Calvo, Gaetano Maugeri, Dafne Bongiorno, Giuseppe Migliorisi, Stefania Stefani

“…Scientific data recently reported carbapenemase variants’ worldwide diffusion and several double-carbapenemases reports. …”
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A Computable Phenotype Algorithm for Postvaccination Myocarditis/Pericarditis Detection Using Real-World Data: Validation Study by Matthew Deady, Raymond Duncan, Matthew Sonesen, Renier Estiandan, Kelly Stimpert, Sylvia Cho, Jeffrey Beers, Brian Goodness, Lance Daniel Jones, Richard Forshee, Steven A Anderson, Hussein Ezzeldin

“…MethodsWe detected cases by sharing and applying computable phenotype algorithms to real-world data in health care providers’ electronic health records databases. …”
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Data mining–based analysis to explore the application of an animal model of diabetic gastroparesis by Hui Xu, Fu-rui Miao, Yu-jun He, Yu-shan Fan

“…Modeling methods primarily included a one-time injection of streptozotocin (60–65 mg/kg) to induce type 1 diabetic gastroparesis or a one-time injection of streptozotocin (40–55 mg/kg) combined with a high-sugar and high-fat irregular diet to induce type 2 diabetic gastroparesis. Most studies set the modeling period as 8 weeks after drug administration. …”
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