Firefly Algorithm based Feature Selection for Arabic Text Classification by Souad Larabi Marie-Sainte, Nada Alalyani

“…However, it has not been involved in feature selection concept to deal with Arabic Text Classification. To validate this technique, Support Vector Machine classifier is used as well as three evaluation measures including precision, recall and F-measure. …”
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Data Augmentation-Driven Improvements in Malignant Lymphoma Image Classification by Sandi Baressi Šegota, Vedran Mrzljak, Ivan Lorencin, Nikola Anđelić

“…This study investigates the impact of a novel augmentation approach on the classification performance of malignant lymphoma histopathological images. …”
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Semantic Patent Classification Using Stack Generalization of Deep Models by Shahla Nemati

“…To solve this issue, we have introduced a deep ensemble model for semantic paragraph-level pattern classification based on the semantic content of patents. …”
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A study on the classification and prediction of firefighter's operational fatigue level. by Mingwei Xu, Shangxue Yang, Ke Wang, Chengliu Yu, Guanlin Liu, Chao Dai, Ruiqi Wang

“…A five-level fatigue classification was established using K-means clustering, and entropy weight analysis was applied to define a comprehensive fatigue index (F), enabling a three-tier fatigue classification: light, moderate, and severe fatigue. …”
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Establishing Two-Dimensional Dependencies for Multi-Label Image Classification by Jiuhang Wang, Yuewen Zhang, Tengjing Wang, Hongying Tang, Baoqing Li

“…As a fundamental upstream task, multi-label image classification (MLIC) work has made a great deal of progress in recent years. …”
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A Crime Data Analysis of Prediction Based on Classification Approaches by Fatima Shaker Hussain, Abbas Fadhil Aljuboori

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Legal Classification of Employment Relations of State Bureau of Investigation Personnel by D. Ye. Zherebtsov

“…The scholarly contributions regarding the classification of service relations within law enforcement agencies are analyzed. …”
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An Overview and Classification of Machine Learning Approaches for Radar Signal Deinterleaving by Louis Lesieur, Jean-Marc Le Caillec, Ali Khenchaf, Vincent Guardia, Abdelmalek Toumi

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Automated Deadlift Techniques Assessment and Classification Using Deep Learning by Wegar Lien Grymyr, Isah A. Lawal

“…To address these concerns, we developed an application designed to classify three distinct styles of deadlifts: conventional, Romanian, and sumo. …”
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Fast SVM-based Multiclass Classification in Large Training Sets by M. Yu. Kurbakov, V. V. Sulimova

“…This paper addresses the actual problem of multiclass classification in large training sets. Classical Support Vector Machines (SVM) is a popular, convenient and well-interpreted classification method, but it has a high computational complexity of a training stage in a nonlinear case and a low data parallelism. …”
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Frequency-Domain Guided Image Classification With Large Model Assistance by Xia Hua, Lei Han

“…Image classification technology has made significant advancements, but methods tailored for specific image classification, such as sport image, remain inadequate. …”
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Multimodal Brain Tumor Classification Using Convolutional Tumnet Architecture by M. Padma Usha, G. Kannan, M. Ramamoorthy

“…In the other case, Tumnet is also applied for single-modal MRI/CT (561 image slices) for classification. The proposed Tumnet was modeled with 5 convolutional layers, 3 pooling layers with ReLU activation function, and 3 fully connected layers. …”
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Classification of Red Blood Cells in the Kendall Space of Reflection Shapes by Ximo Gual-Arnau, Lluïsa Gual-Vayà

“…The classification of red blood cells (RBCs) or erythrocytes into three categories based on their shape, normal, sickle-shaped, and those with other deformations, has proven to be a crucial tool in diagnosing and managing sickle cell disease (SCD). …”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

“…Based on the different IR absorption spectrum bands produced by each kind of lubricating grease, the three-dimensional spatial distribution map of the lubricating grease drawn also verifies the accuracy of classification while recognizing the accuracy. …”
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SMOTEHashBoost: Ensemble Algorithm for Imbalanced Dataset Pattern Classification by Seema Yadav, Dhruvanshu Joshi, Soham Mulye, Sandeep S. Udmale, Girish P. Bhole

“…Class imbalance occurs frequently in machine learning, particularly in binary classification tasks where the majority class has a significantly larger number of samples than the minority class. …”
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In-context learning for label-efficient cancer image classification in oncology by Mobina Shrestha, Bishwas Mandal, Vishal Mandal, Asis Shrestha, Amir Babu Shrestha

“…To the best of our knowledge, this is the first study to compare the performance of multiple VLMs with in-context learning on different oncology classification tasks. Without any parameter updates, all models showed significant gains with few-shot prompting, with GPT-4o reaching an F1 score of 0.81 in binary classification and 0.60 in multi-class classification settings. …”
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Enhancing driver emotion recognition through deep ensemble classification by Faizan Zaman, Zhigang Xu, Adil Hussain, Anees Ullah, Khalid Zaman

“…Features are extracted from three CNN models and merged via advanced techniques to create an ensemble classification model. …”
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Fault Detection and Classification of Power Plant Using Neural Networks by Rawaa J. Hussein, Khalaf S. Gaeid, Amin Al-Habaibeh

“…The model represents a three-phase power system network comprising two units. …”
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Novel Classification of Posttraumatic Ear Deformities and its Surgical Management by Umesh Kumar, P. Jain

“…Background Classification of posttraumatic ear deformities and its reconstruction is an uphill task for a reconstructive surgeon as they present in various combinations. …”
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Transformer-based ensemble model for dialectal Arabic sentiment classification by Omar Mansour, Eman Aboelela, Remon Talaat, Mahmoud Bustami

“…This form of analysis, also referred to as sentiment classification, opinion mining, emotion mining, and review mining, is the focus of this study, which analyzes tweets from three benchmark datasets: the Arabic Sentiment Tweets Dataset (ASTD), the A Twitter-based Benchmark Arabic Sentiment Analysis Dataset (ASAD), and the Tweets Emoji Arabic Dataset (TEAD). …”
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