ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias by Hongzhen Cui, Shenhui Ning, Shichao Wang, Wei Zhang, Yunfeng Peng

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Dual-Priority Delayed Deep Double Q-Network (DPD3QN): A Dueling Double Deep Q-Network with Dual-Priority Experience Replay for Autonomous Driving Behavior Decision-Making by Shuai Li, Peicheng Shi, Aixi Yang, Heng Qi, Xinlong Dong

“…Subsequently, dual-priority experience replay is incorporated to facilitate the model’s ability to swiftly recognize and leverage critical experiences. Ultimately, the training and evaluation are conducted on the OpenAI Gym simulation platform. …”
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The Specialist’s Paradox: Generalist AI May Better Organize Medical Knowledge by Carlo Galli, Maria Teresa Colangelo, Marco Meleti, Elena Calciolari

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Unsupervised Temporal Adaptation in Skeleton-Based Human Action Recognition by Haitao Tian, Pierre Payeur

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Adversarial Validation in Image Classification Datasets by Means of Cumulative Spectral Gradient by Diego Renza, Ernesto Moya-Albor, Adrian Chavarro

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Enhanced Curvature-Based Fabric Defect Detection: A Experimental Study with Gabor Transform and Deep Learning by Mehmet Erdogan, Mustafa Dogan

“…The primary contribution of this work is the development of a modified curvature algorithm that achieves high classification performance without the need for training. …”
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Effective Detection of Malicious Uniform Resource Locator (URLs) Using Deep-Learning Techniques by Yirga Yayeh Munaye, Aneas Bekele Workneh, Yenework Belayneh Chekol, Atinkut Molla Mekonen

“…The study involved collecting a dataset of 87,216 URLs, comprising both benign and malicious samples sourced from the open project directory (DMOZ), PhishTank, and Any.Run. Models were trained using the training set and evaluated on the test set using standard metrics, including accuracy, precision, recall, and F1-score. …”
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Optimized Energy Consumption of Electric Vehicles with Driving Pattern Recognition for Real Driving Scenarios by Bedatri Moulik, Sanmukh Kaur, Muhammad Ijaz

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Prompt Once, Segment Everything: Leveraging SAM 2 Potential for Infinite Medical Image Segmentation with a Single Prompt by Juan D. Gutiérrez, Emilio Delgado, Carlos Breuer, José M. Conejero, Roberto Rodriguez-Echeverria

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An Autoencoder-Based Task-Oriented Semantic Communication System for M2M Communication by Prabhath Samarathunga, Hossein Rezaei, Maheshi Lokumarambage, Thushan Sivalingam, Nandana Rajatheva, Anil Fernando

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Deephive: A Reinforcement Learning Approach for Automated Discovery of Swarm-Based Optimization Policies by Eloghosa Ikponmwoba, Opeoluwa Owoyele

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Advancements in Machine Learning-Based Intrusion Detection in IoT: Research Trends and Challenges by Márton Bendegúz Bankó, Szymon Dyszewski, Michaela Králová, Márton Bertalan Limpek, Maria Papaioannou, Gaurav Choudhary, Nicola Dragoni

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Electric Vehicle Sales Forecast for the UK: Integrating Machine Learning, Time Series Models, and Global Trends by Shima Veysi, Mohammad Moshfeghi, Amir Sadrfaridpour, Peiman Emamy

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Self-Supervised Keypoint Learning for the Geometric Analysis of Road-Marking Templates by Chayanon Sub-r-pa, Rung-Ching Chen

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Clinical Validation of a Computed Tomography Image-Based Machine Learning Model for Segmentation and Quantification of Shoulder Muscles by Hamidreza Rajabzadeh-Oghaz, Josie Elwell, Bradley Schoch, William Aibinder, Bruno Gobbato, Daniel Wessell, Vikas Kumar, Christopher P. Roche

“…The validation evaluates the quality of the auto-segmented deltoid images. …”
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Expanded Design by Roberto Bottazzi

“…Contrary to previous algorithmic processes, machine learning models must be trained before they are deployed. …”
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A complete, multi-layered quranic treebank dataset with hybrid syntactic annotations for classical arabic processingMendeley Data by Wadee A. Nashir, Abdulqader M. Mohsen, Asma A. Al-Shargabi, Mohamed K. Nour, Badriyya B. Al-onazi

“…EQTB offers significant reuse potential, providing crucial training/evaluation data for diverse CA NLP tasks (parsing, morphology, diacritization), supporting linguistic research, and enabling the development of advanced pedagogical tools and language technologies.…”
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The Quality of HOTS-Based Science Questions Developed by Indonesian Elementary School Teachers by Naufal Ishartono, Anatri Desstya, Harun Joko Prayitno, Yasir Sidiq

“…Hopefully, this study's findings can be an evaluation material for policymakers in education to increase the training quality of HOTS-based science questions for elementary school level in Indonesia. …”
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A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning by Ruoyu Sun, Yue Xi, Angelos Stefanidis, Zhengyong Jiang, Jionglong Su

“…Furthermore, we find that adopting the auxiliary agent and HDRL training algorithm can efficiently overcome the issue of the curse of dimensionality and improve the training efficiency in the positive reward sparse environment. …”
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Two hours in Hollywood: A manually annotated ground truth data set of eye movements during movie clip watching by Ioannis Agtzidis, Mikhail Startsev, Michael Dorr

“…In these labels, 62.4% of the samples were attributed to fixations, 9.1% – to saccades, and, notably, 24.2% – to pursuit (the remainder marked as noise). After evaluation of 15 published eye movement classification algorithms on our newly collected annotated data set, we found that the most recent algorithms perform very well on average, and even reach human-level labelling quality for fixations and saccades, but all have a much larger room for improvement when it comes to smooth pursuit classification. …”
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