Hybrid transformer-CNN and LSTM model for lung disease segmentation and classification by Syed Mohammed Shafi, Sathiya Kumar Chinnappan

“…Approximately three million individuals are affected with various types of lung disorders annually. This issue alarms us to take control measures related to early diagnostics, accurate treatment procedures, etc. …”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…The dataset exhibited a problem of class imbalance, with the majority class (non-mastitis cases) being over-represented. To address this issue, an undersampling algorithm was applied to balance the class distribution by removing a portion of the majority class data. …”
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Phytoplankton group classification by integrating trait information and observed environmental thresholds by Hoang Vuong Dang, Kermode Stephanie, Peisheng Huang, Cayelan C. Carey, Matthew R. Hipsey

“…Third, we applied K-prototype clustering for group classification based on the identified thresholds and associated traits. …”
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Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification by Lochana Mendis, Debjyoti Karmakar, Marimuthu Palaniswami, Fiona Brownfoot, Emerson Keenan

“…Efforts to address this issue have focused on data-driven deep-learning methods to detect fetal compromise automatically. …”
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Comparative Analysis of Vision Transformers and CNN Models for Driver Fatigue Classification by Fadhlan Hafizhelmi Kamaru Zaman, Kok Mun Ng, Syahrul Afzal Che Abdullah

“… This study provides a comprehensive evaluation of Convolutional Neural Network (CNN) and Vision Transformer (ViT) models for driver fatigue classification, a critical issue in road safety. Using a custom driving behavior dataset, state-of-the-art CNN and ViT architectures, including VGG16, EfficientNet, MobileNet, Inception, DenseNet, ResNet, ViT, and Swin Transformer, were analyzed in this study to determine the best model for practical driver fatigue monitoring systems. …”
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The knowledge organisation of sub-subgenres: the curious case of the collaborative works of Gilbert and Sullivan by Deborah Lee

“…This paper explores the knowledge organisation of sub-subgenres and takes a micro-level approach to genre classification. The study uses a particular case study: the classification issues around the collaborative works of Gilbert and Sullivan.  …”
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A Feature Selection Approach to the Group Behavior Recognition Issue Using Static Context Information by Alberto Pozo, Miguel A. Patricio, Jesús García, José Manuel Molina

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Do Indian Researchers Consider Functioning Issues of Lower Extremity Osteoarthritis: A Scoping Review by P. Ratan Khuman, Balaganapathy Muruganantham

“…This scoping review describes the nature and extent to which the Indian researchers considered the functioning issues of LEOA individuals and linked them with the International Classification of Functioning, Disability, and Health (ICF) categories. …”
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Prevalence of psychotic disorders and its association with methodological issues. A systematic review and meta-analyses. by Berta Moreno-Küstner, Carlos Martín, Loly Pastor

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Binary classification with Fuzzy-Bayesian logistic regression using Gaussian fuzzy numbers by Georgios Charizanos, Haydar Demirhan, Duygu İçen

“…Binary classification is a critical task in pattern recognition applications in artificial intelligence and machine learning. …”
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ADeepWeeD: An adaptive deep learning framework for weed species classification by Md Geaur Rahman, Md Anisur Rahman, Mohammad Zavid Parvez, Md Anwarul Kaium Patwary, Tofael Ahamed, David A. Fleming-Muñoz, Saad Aloteibi, Mohammad Ali Moni, PhD

“…To address the issues, this paper introduces a novel DL-based framework called ADeepWeeD for weed classification that facilitates adaptive (i.e. incremental) learning so that it can handle new weed species by keeping track of historical information. …”
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CNN-Based Image Segmentation Approach in Brain Tumor Classification: A Review by Nurul Huda, Ku Ruhana Ku-Mahamud

“…CNN architectures like U-Net, V-Net, and ResNet have shown significant promise in brain tumor classification, offering high precision in detecting tumor boundaries and classifying tumor types. …”
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Training RBF NN Using Sine-Cosine Algorithm for Sonar Target Classification by Yixuan WANG, LiPing YUAN, Mohammad KHISHE, Alaveh MORIDI, Fallah MOHAMMADZADE

“…Radial basis function neural networks (RBF NNs) are one of the most useful tools in the classification of the sonar targets. Despite many abilities of RBF NNs, low accuracy in classification, entrapment in local minima, and slow convergence rate are disadvantages of these networks. …”
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Land Take: from Fabric Classification to identifying Areas for Sustainable Urban Regeneration by Santini Luisa, Ducci Elisa

“…In addition, it prescribes that the delimitation of urbanized territory must start from the classification of urban fabric in relation to codified morphotypes of contemporary urbanizations. …”
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Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…Although the biometric identification systems have advanced, the existing approaches still struggle with accuracy, overfitting issues and computational efficiency, especially when utilizing periocular images for person identification and gender classification. …”
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Nutrient deficiency detection and classification in coffee leaves using deep learning models by Randive Lalita, Sapkal Shubhangi, Bornare Deepak

“…Early detection and treatment are crucial for addressing these issues. Essential nutrients like nitrogen, phosphorus, and potassium are crucial for coffee plant growth. …”
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Two-Stage Fault Classification Algorithm for Real Fault Data in Transmission Lines by Se-Heon Lim, Taegeun Kim, Kyeong-Yeong Lee, Kyung-Min Song, Sung-Guk Yoon

“…Fault classification in power transmission lines is important in distance relaying for identifying the accurate phases implicated in the fault occurrence. …”
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Comparative Analysis of Different Efficient Machine Learning Methods for Fetal Health Classification by Md Takbir Alam, Md Ashibul Islam Khan, Nahian Nakiba Dola, Tahia Tazin, Mohammad Monirujjaman Khan, Amani Abdulrahman Albraikan, Faris A. Almalki

“…Machine learning (ML) is currently extensively used in fields such as biology and medicine to address a variety of issues, due to its fast advancement. This research covers the findings and analyses of multiple machine learning models for fetal health classification. …”
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Patterns with Equal Values in Permutation Entropy: Do They Really Matter for Biosignal Classification? by David Cuesta–Frau, Manuel Varela–Entrecanales, Antonio Molina–Picó, Borja Vargas

“…A number of variations or customizations to the original PE method to address these issues have been proposed in the scientific literature recently. …”
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Enhancing mental health diagnostics through deep learning-based image classification by Lixin Zhang, Ruotong Zeng

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