Boosting Crowdsourced Annotation Accuracy: Small Loss Filtering and Augmentation-Driven Training by Yanming Fu, Weigeng Han, Jingsang Yang, Haodong Lu, Xin Yu

“…However, the labels provided by untrained crowdsourcing workers often contain a considerable amount of noise. Although the application of ground truth inference algorithms to deduce integrated labels effectively enhances label quality, a certain level of noise persists. …”
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. by André G Coimbra, Cleiane G Oliveira, Matheus P Libório, Hasheem Mannan, Laercio I Santos, Elisa Fusco, Marcos F S V D'Angelo

“…This study conducts a comparative analysis of techniques for handling imbalanced data and evaluates their effectiveness in combination with a set of classification algorithms, specifically focusing on stroke prediction. …”
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Machine Learning Approaches to Code Similarity Measurement: A Systematic Review by Zixian Zhang, Takfarinas Saber

“…Following a rigorous systematic review protocol, we identified and analyzed 84 primary studies on a broad spectrum of dimensions covering application type, devised Machine Learning algorithms, used code representations, datasets, and performance metrics, as well as performance evaluations. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…Abstract This study addresses key challenges in optimizing agricultural industry structures and facilitating intelligent transformation through the application of deep learning algorithms and advanced optimization techniques. …”
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An Efficient Biobjective Heuristic for Scheduling Workflows on Heterogeneous DVS-Enabled Processors by Pengji Zhou, Wei Zheng

“…Energy consumption has recently become a major concern to multiprocessor computing systems, of which the primary performance goal has traditionally been reducing execution time of applications. In the context of scheduling, there have been increasing research interests on algorithms using dynamic voltage scaling (DVS), which allows processors to operate at lower voltage supply levels at the expense of sacrificing processing speed, to acquire a satisfactory trade-off between quality of schedule and energy consumption. …”
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Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning by Fang Nan, Chao Zeng, Huanfeng Shen, Liupeng Lin

“…This study focuses on an internet of things (IoT) application in Wuhan, China, aiming to enhance the quality of long-term hourly air temperature data collected by low-cost sensors through on-site calibration. …”
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Dataset for estimating reinforcement, width and penetration of the weld bead in the GMAW process using thermographic informationfigshare by Bruno Mota de Souza, Guillermo Alvarez Bestard, Sadek C. Absi Alfaro

“…In pursuit of smarter and more efficient welding methods, assessing the quality of welded components remains critical but is often constrained by traditional destructive testing methods for evaluating production batches. …”
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Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports by Sophia Wesely, Ella Hofer, Robin Curth, Shyam Paryani, Nicole Mills, Olaf Ueberschär, Julia Westermayr

“…Using triaxial accelerations and rotational speeds, various ML algorithms were employed to classify and evaluate the execution of tumbling manoeuvres. …”
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Image Preprocessing Framework for Time-domain Astronomy in the Artificial Intelligence Era by Liang Cao, Peng Jia, Jiaxin Li, Yu Song, Chengkun Hou, Yushan Li

“…Image preprocessing, which involves standardizing images for training or deployment of various AI algorithms, encompasses essential steps such as image quality evaluation, alignment, stacking, background extraction, gray-scale transformation, cropping, source detection, astrometry, and photometry. …”
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A Review of Developments and Metrology in Machine Learning and Deep Learning for Wearable IoT Devices by Minh Long Hoang

“…It also examines how algorithm selection influences model performance metrics and computational efficiency, which are critical for real-time and resource-constrained applications. …”
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Role of artificial intelligence in healthcare insurance: systematic literature review by Ahmed Ali Alkhelb, Salah Alshagrawi

“…Background: The use of artificial intelligence (AI) has been shown to enhance human life quality by making it easier, safer, and more efficient. …”
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Multistage Threshold Segmentation Method Based on Improved Electric Eel Foraging Optimization by Yunlong Hu, Liangkuan Zhu, Hongyang Zhao

“…To evaluate the segmentation performance of the proposed MIEEFO, 15 benchmark functions are used, and comparisons are made with seven other algorithms. …”
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Automation Applied to the Collection and Generation of Scientific Literature by Nadia Paola Valadez-de la Paz, Jose Antonio Vazquez-Lopez, Aidee Hernandez-Lopez, Jaime Francisco Aviles-Viñas, Jose Luis Navarro-Gonzalez, Alfredo Valentin Reyes-Acosta, Ismael Lopez-Juarez

“…The approach included a panel of experts who confirmed the algorithm’s effectiveness in identifying source words in high-quality articles. …”
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A BERT-Based Classification Model: The Case of Russian Fairy Tales by Валерий Дмитриевич Соловьев, Марина Ивановна Солнышкина, Andrey Ten, Николай Аркадиевич Прокопьев

“…Method: We pre-train BERT using a collection of three classes of documents and fine-tune it for implementation of a specific application task. Focused on the mechanism of tokenization and embeddings design as the key components in BERT’s text processing, the research also evaluates the standard benchmarks used to train classification models and analyze complex cases, possible errors and improvement algorithms thus raising the classification models accuracy. …”
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Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…In this research, we conducted a Systematic Mapping Study (SMS), examining the types of unsupervised algorithms implemented in developed models and thoroughly exploring the evaluation metrics employed. …”
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Prospects of cold plasma in enhancing food phenolics: analyzing nutritional potential and process optimization through RSM and AI techniques by M. Anjaly Shanker, Sandeep Singh Rana

“…Among these techniques, cold plasma would be an operative choice in plant-based applications due to their higher efficacy, greenness, chemical exclusivity, and quality retention. …”
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Reliable Graph Routing in Industrial Wireless Sensor Networks by Jing Zhao, Yajuan Qin, Dong Yang, Junqi Duan

“…Our design is evaluated using simulation where we show that our algorithm could achieve a balance between routing reliability and overhead.…”
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A Big-Data-Driven Framework for Parking Demand Estimation in Urban Central Districts by Yunlin Guan, Yun Wang, Xuedong Yan, Haonan Guo, Yu Zhou

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Outliers and anomalies in training and testing datasets for AI-powered morphometry—evidence from CT scans of the spleen by Yuriy Vasilev, Yuriy Vasilev, Anastasia Pamova, Tatiana Bobrovskaya, Anton Vladzimirskyy, Anton Vladzimirskyy, Olga Omelyanskaya, Elena Astapenko, Artem Kruchinkin, Novik Vladimir, Kirill Arzamasov, Kirill Arzamasov

“…There are no universally accepted methods for evaluating outliers or anomalies in such datasets. This can cause errors in machine learning and compromise the quality of end products. …”
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First study of the RuPatient health information system with optical character recognition of medical records based on machine learning by A. A. Komkov, V. P. Mazaev, S. V. Ryazanova, D. N. Samochatov, E. V. Koshkina, E. V. Bushueva, O. M. Drapkina

“…We compared the recognition quality of RuPatient HIS and a popular optical character recognition application (FineReader for Mac).Results. …”
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