A dataset for vineyard disease detection via multispectral imagingZenodo by Alessio Saccuti, Filippo Graziosi, Dario Lodi Rizzini

“…The dataset includes raw and processed images, calibration images for the multispectral camera, annotations detailing plant health conditions, and Python-based usage examples for researchers. Potential applications include the development of machine learning algorithms for automated disease detection, image alignment techniques, and background removal methods. …”
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Simulation Analysis of Control Strategy for Doubly-fed Induction Generators by 李大虎, 石新春

“…The maximum wind tracking and operational characteristics of grid are researched under the simulation model. The simulation results prove the validity of control algorithms and good control performance.…”
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THE CLASS OF PERFECT TERNARY ARRAYS by A. V. Sokolov, O. N. Zhdanov

“…In recent decades, perfect algebraic constructions are successfully being use to signal systems synthesis, to construct block and stream cryptographic algorithms, to create pseudo-random sequence generators as well as in many other fields of science and technology. …”
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Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data by Marco Stock, Corinna Losert, Matteo Zambon, Niclas Popp, Gabriele Lubatti, Eva Hörmanseder, Matthias Heinig, Antonio Scialdone

“…Finally, we propose a standardized benchmarking framework to evaluate algorithms more fairly, ensuring biologically meaningful comparisons. …”
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Leveraging transformers and explainable AI for Alzheimer's disease interpretability. by Humaira Anzum, Nabil Sadd Sammo, Shamim Akhter

“…To detect Alzheimer's disease, brain scans such as computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET) can be performed. Many researches have been undertaken to use computer vision on MRI images, and their accuracy ranges from 80-90%, new computer vision algorithms and cutting-edge transformers have the potential to improve this performance.We utilize advanced transformers and computer vision algorithms to enhance diagnostic accuracy, achieving an impressive 99% accuracy in categorizing Alzheimer's disease stages through translating RNA text data and brain MRI images in near-real-time. …”
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Deep-learning-based buffalo identification through muzzle pattern images by O. Ermetin, H. K. Örnek

“…Accurate identification of buffaloes is crucial for producers and researchers to maintain records and ensure effective tracking. …”
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Energy Trading in Local Energy Markets: A Comprehensive Review of Models, Solution Strategies, and Machine Learning Approaches by Sania Khaskheli, Amjad Anvari-Moghaddam

“…State-of-the-art reinforcement learning algorithms are classified into model-free and model-based methods. …”
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BESS-Set: A Dataset for Cybersecurity Monitoring in a Battery Energy Storage System by Giovanni Battista Gaggero, Alessandro Armellin, Giulio Ferro, Michela Robba, Paola Girdinio, Mario Marchese

“…In this context, there is a need to develop datasets of attacks on these systems to evaluate the risks and allow researchers to develop proper monitoring algorithms. …”
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Author Identification Systems. by A. Ben Wagner

“…This paper reviews a number of operational and in-development services. Some systems like ResearcherId.Com depend on self-registration and self-identification of a researcher's articles. …”
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Multistable Physical Neural Networks by Ben‐Haim Eran, Givli Sefi, Or Yizhar, Gat D. Amir

“…Building on these maps, both global and local algorithms for training multistable PNNs are implemented. …”
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CRISP: correlation-refined image segmentation process by Jennifer K. Briggs, Erli Jin, Matthew J. Merrins, Richard K. P. Benninger

“…To assess the activity of individual cells, researchers must segment images into the individual cells. …”
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StopSpamX: A multi modal fusion approach for spam detection in social networking by Dasari Siva Krishna, Gorla Srinivas

“…In order to achieve a spam free environment, researchers have proposed numerous methods and algorithms for spam detection. …”
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In-Depth Analysis of Various Artificial Intelligence Techniques in Software Engineering: Experimental Study by Mohd Mustaqeem, Tamanna Siddiqui, Najeeb Ahmad Khan, Deepak Kumar

“…Our manuscript shows various AI-based algorithms that include Machine learning techniques (ML), Artificial Neural Networks (ANN), Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), Natural Language Processing (NLP), Genetic Algorithms (GA) applications. …”
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Blockchain Approaches Survey for Big Data: Systematic Study, Challenges and Innovations by Sila Yavuz, Enes Korkmaz

“…In recent years, the decentralization of an environment has been extensively studied by various researchers. Blockchain as an environment of decentralized technology, with its unique features such as irreversible structure and high data security, has attracted the attention of many researchers. …”
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Machine Learning Applied to Reference Signal-Less Detection of Motion Artifacts in Photoplethysmographic Signals: A Review by Erick Javier Argüello-Prada, Javier Ferney Castillo García

“…Machine learning algorithms have brought remarkable advancements in detecting motion artifacts (MAs) from the photoplethysmogram (PPG) with no measured or synthetic reference data. …”
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Distributed Prescribed Finite Time Consensus Scheme for Economic Dispatch of Smart Grids with the Valve Point Effect by Yingjiang Zhou, Shigao Zhu, Qian Chen

“…Finally, from the simulations, the efficiency of the proposed algorithms is validated.…”
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Excavation Safety Modeling Approach Using BIM and VPL by Numan Khan, Ahmad K. Ali, Miroslaw J. Skibniewski, Do Yeop Lee, Chansik Park

“…They have developed various algorithms to enhance safety in preconstruction phase such as automated generation of scaffolding and its potential risk analysis, checking BIM model for fall risks, and limited access zone allocation in wall masonry. …”
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A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade by Attila Kovari

“…Artificial intelligence tools, in particular machine learning, natural language processing and recommender algorithms, facilitate collaborative learning by enabling personalized learning through feedback and group work. …”
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Dimensionality Reduction problem: a Comprehensive Exploration of Disjoint Principal Component Analysis (DPCA) and Disjoint Multiple Correspondence Analysis (DMCA) by Mario Fordellone

“…We navigate through the intricacies of their algorithms and explore how they unveil patterns within complex datasets. …”
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Machine Learning in Microwave Medical Imaging and Lesion Detection by Wenyi Shao

“…Machine learning (ML) techniques have attracted many microwave researchers and engineers for their potential to improve performance in microwave- and millimeter-wave-based medical applications. …”
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