Transfer Learning-Based Ensemble of CNNs and Vision Transformers for Accurate Melanoma Diagnosis and Image Retrieval by Murat Sarıateş, Erdal Özbay

“…<b>Results</b>: Experimental evaluations demonstrated that the proposed Ensemble model significantly outperformed each standalone model in both classification and retrieval tasks. …”
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Sunrise in the Desert: Leveraging Big Data Analytics for Predictive Solar Energy Production in Saudi Arabia by Da'ad Albahdal, Maha Almousa, Wijdan Aljebreen, Aeshah A. Almutairi

“…Using meteorological variables, including air conditions, wind patterns, relative humidity, and barometric pressure from 44 stations, we evaluated three machine learning models&#x2014;Linear Regression (LR), Support Vector Regression (SVR), and Decision Tree (DT)&#x2014;for predicting daily solar radiation. …”
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Microgrid Load Forecasting Based on Improved Long Short-Term Memory Network by Qiyue Huang, Yuqing Zheng, Yuxuan Xu

“…And a complete forecasting model is designed to accomplish the load forecasting. …”
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Co-translation, consultancy and joint authorship: User-centred translation and editing in collaborative audio description by Maija Hirvonen, Marika Hakola, Michael Klade

“…Findings from a microethnographic analysis of authentic work processes of team AD in three countries are presented: these include the definition of different types of team AD (a translation approach and an editing approach), and various perspectives to collaboration (co-translation, joint problem-solving and decision-making, joint authorship). …”
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Tourist Destination Recommendations Using Deep Learning by Amarita Ritthipakdee, Chartchai Leenawong

“…By categorizing tourists based on their interests and recommending destinations accordingly, the model supports more informed and personalized travel decision-making. …”
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A network-based approach on detecting dredgers’ illegal behavior of dumping dredged sediments by Rongxin Zhang, Fei Yuan, En Cheng

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Intrusion Detection in IoT and IIoT: Comparing Lightweight Machine Learning Techniques Using TON_IoT, WUSTL-IIOT-2021, and EdgeIIoTset Datasets by Shereen Ismail, Salah Dandan, Ala'a Qushou

“…The performance of Decision Tree (DT), Random Forest (RF), and three ensemble techniques: Bagging, Stacking, and LightGBM (LGBM), was evaluated. …”
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Interpretable artificial intelligence (AI) for cervical cancer risk analysis leveraging stacking ensemble and expert knowledge by Priyanka Roy, Mahmudul Hasan, Md Rashedul Islam, Md Palash Uddin

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A Sensory Glove With a Limited Number of Sensors for Recognition of the Finger Alphabet of Polish Sign Language by Jakub Piskozub, Pawel Strumillo

“…The influence hierarchy of individual piezoelectric sensors was determined using a decision tree algorithm during previous stage of research, which achieved 94% accuracy with data from only three sensors. …”
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A review of deep learning methods in aquatic animal husbandry by Marzuraikah Mohd Stofa, Fatimah Az Zahra Azizan, Mohd Asyraf Zulkifley

“…This article focuses on the use of deep learning in three key areas: classification, localization, and segmentation. …”
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Intratumoral and peritumoral radiomics for forecasting microsatellite status in gastric cancer: a multicenter study by Yunzhou Xiao, Jianping Zhu, Huanhuan Xie, Zhongchu Wang, Zhaohai Huang, Miaoguang Su

“…After standardizing and reducing the dimensionality of these features, six radiomic models were constructed utilizing three machine learning techniques: Support Vector Machine (SVM), Linear Support Vector Classification (LinearSVC), and Logistic Regression (LR). …”
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A novel methodological approach to SaaS churn prediction using whale optimization algorithm. by Muhammed Kotan, Ömer Faruk Seymen, Levent Çallı, Sena Kasım, Burcu Çarklı Yavuz, Tijen Över Özçelik

“…These three datasets were examined with the most used in literature, k-nearest neighbor, Decision Trees, Naïve Bayes, Random Forests, and Neural Network techniques, and the performance metrics such as Area Under Curve, Accuracy, Precision, Recall, and F1 Score were used as classification success. …”
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BAYESIAN ADDITIVE REGRESSION TREE APPLICATION FOR PREDICTING MATERNITY RECOVERY RATE OF GROUP LONG-TERM DISABILITY INSURANCE by Stevanny Budiana, Felivia Kusnadi, Robyn Irawan

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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…This study induced AI classification models with different biases. The model with the best fit was Random Forest with a 0.83 AUC. …”
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Determining Solution Space Characteristics for Real-Time Strategy Games and Characterizing Winning Strategies by Kurt Weissgerber, Gary B. Lamont, Brett J. Borghetti, Gilbert L. Peterson

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Alfalfa stem count estimation using remote sensing imagery and machine learning on Google Earth Engine by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Md Saifuzzaman, Rami Albasha, Maxime Leduc

“…Our proposed framework model can offer valuable information to growers and decision-makers, enabling them to make timely and informed decisions.…”
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Cognitive Radio Transceivers: RF, Spectrum Sensing, and Learning Algorithms Review by Lise Safatly, Mario Bkassiny, Mohammed Al-Husseini, Ali El-Hajj

“…Moreover, we study unsupervised classification algorithms and a reinforcement learning (RL) algorithm that has been proposed to perform decision-making in CR networks.…”
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Assessing the Reliability of Seasonal Data in Representing Synoptic Weather Types: A Mediterranean Case Study by Alexandros Papadopoulos Zachos, Kondylia Velikou, Errikos-Michail Manios, Konstantia Tolika, Christina Anagnostopoulou

“…Model evaluation indicates that seasonal forecasts achieve an accuracy of approximately 80% in predicting the daily synoptic condition (cyclonic or anticyclonic) up to three months in advance. …”
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Solving Simulated Imbalanced Body Performance Data using A-SUWO and Tomek Link Algorithm by Febryan Grady, Joel Rizky Wahidiyat, Abba Suganda Girsang

“… This research examines the impact of various sampling techniques on the performance of classification models in the context of imbalanced datasets, employing the body performance dataset as a case study.  …”
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