Parkgoers go to the virtual park: a classification framework, systematic review, and future tourism research agenda by Aniesa Samira Bafadhal, Faiz Izwan Anuar, Mohd Hafiz Hanafiah

“…The framework comprehensively covered current issues and future developments in virtual park research, providing a foundation for future studies.Discussion This is the first study that represents a pioneering effort in developing a virtual theme park framework and reviewing virtual parks within the tourism context. …”
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Improving Gaussian Naive Bayes classification on imbalanced data through coordinate-based minority feature mining by Wei Wang, Li Yan, Fen Liu, Yanxi Li

“…As a widely used classification model, the Gaussian Naive Bayes (GNB) classifier experiences a significant decline in performance when handling imbalanced data. …”
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Innovative Approach for Diabetic Retinopathy Severity Classification: An AI-Powered Tool using CNN-Transformer Fusion by Khosro Rezaee, Fateme Farnami

“…While deep learning has advanced DR diagnosis, many models face issues like inconsistent performance, limited datasets, and poor interpretability, reducing their clinical utility. …”
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SSL-MBC: Self-Supervised Learning With Multibranch Consistency for Few-Shot PolSAR Image Classification by Wenmei Li, Hao Xia, Bin Xi, Yu Wang, Jing Lu, Yuhong He

“…Based on the abovementioned issues, we propose an SSL model with multibranch consistency (SSL-MBC) for few-shot PolSAR image classification. …”
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A Transfer Learning-Based Framework for Enhanced Classification of Perceived Mental Stress Using EEG Spectrograms by Sheharyar Khan, Sadam Hussain Noorani, Jaroslav Frnda, Usman Rauf, Aamir Arsalan, Sanay Muhammad Umar Saeed

“…Prolonged exposure to stress can lead to numerous physical health issues, including cardiovascular diseases, and a weakened immune system. …”
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Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification by Prathibanandhi Jeyashanker, Annie Grace Vimala Georgewilliam Sundaram, Padmakala Sadagopan, Abid Yahya, Ravi Samikannu, Irfan Anjum Badruddin, Sarfaraz Kamangar, Mohamed Ghouse Shukur

“…The main objective of this paper is to address these important issues by proposing a deep learning model, Holographic Convolutional Dense Network (Coco-HoloNet) that will be tailored for the precise detection and classification of PCOD in ultrasound images with high accuracy. …”
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False data injection attack dataset for classification, identification, and detection for IIoT in Industry 5.0Zenodo by A K M Ahasan Habib, Mohammad Kamrul Hasan, Rosilah Hassan, Shayla Islam, Huda Saleh Abbas

“…The new Industry 5.0 era of interaction and accessibility has been brought about by the widespread use of Industrial Internet of Things (IIoT) devices, however, it also has uncovered several security issues, with False Data Injection (FDI) attacks being a significant concern. …”
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PyionNet: Pyramid Progressive Cross-Fusion Network for Joint Classification of Hyperspectral and LiDAR Data by Haizhu Pan, Quanxiu Zhang, Haimiao Ge, Moqi Liu, Cuiping Shi

“…To address these issues, this article proposes a pyramid progressive cross-fusion network, named PyionNet, for joint classification of HS and LiDAR data. …”
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Multi-Feature Lightweight DeeplabV3+ Network for Polarimetric SAR Image Classification with Attention Mechanism by Junfei Shi, Shanshan Ji, Haiyan Jin, Yuanlin Zhang, Maoguo Gong, Weisi Lin

“…Besides, multiple features can provide more complementary information, while feature selection is crucial for classification. To address these issues, we propose a novel attention mechanism-based multi-feature lightweight DeeplabV3+ network for PolSAR image classification. …”
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SNet: A novel convolutional neural network architecture for advanced endoscopic image classification of gastrointestinal disorders by Samra Siddiqui, Junaid A. Khan, Tallha Akram, Meshal Alharbi, Jaehyuk Cha, Dina A. AlHammadi

“…The objective of this research is to develop a robust deep network, called SNet, that offers a solution to complex classification problems. Firstly, the endoscopic images undergo preprocessing before being subjected to feature extraction. …”
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Towards Self-Conscious AI Using Deep ImageNet Models: Application for Blood Cell Classification by Mohamad Abou Ali, Fadi Dornaika, Ignacio Arganda-Carreras

“…The exceptional performance of ImageNet competition winners in image classification has led AI researchers to repurpose these models for a whole range of tasks using transfer learning (TL). …”
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Towards precision in IoT-based healthcare systems: a hybrid optimized framework for big data classification by Satheeshkumar Palanisamy, Vigneshwaran Thangaraju, Jeevitha Kandasamy, Ayodeji Olalekan Salau

“…KEYWORDS: Big data, Healthcare, Optimization, Classification, Feature Extraction and COVID-19 database.…”
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CA-ViT: Contour-Guided and Augmented Vision Transformers to Enhance Glaucoma Classification Using Fundus Images by Tewodros Gizaw Tohye, Zhiguang Qin, Mugahed A. Al-antari, Chiagoziem C. Ukwuoma, Zenebe Markos Lonseko, Yeong Hyeon Gu

“…Nevertheless, limited approaches have been suggested to improve glaucoma classification due to issues like inadequate training data, variations in feature distribution, and the overall quality of samples. …”
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Enhanced Gold Ore Classification: A Comparative Analysis of Machine Learning Techniques with Textural and Chemical Data by Fabrizzio Rodrigues Costa, Cleyton de Carvalho Carneiro, Carina Ulsen

“…Specific computational methods, such as machine learning algorithms, can assist mining professionals in quickly and consistently identifying and addressing classification issues related to mineralized horizons, as well as uncovering key variables that impact predictive outcomes, many of which were previously difficult to observe. …”
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Enhancing Cross-Domain Remote Sensing Scene Classification by Multi-Source Subdomain Distribution Alignment Network by Yong Wang, Zhehao Shu, Yinzhi Feng, Rui Liu, Qiusheng Cao, Danping Li, Lei Wang

“…Moreover, relying solely on global alignment risks losing fine-grained information for each class, especially in the task of RS scene classification. To alleviate these issues, we present a Multi-Source Subdomain Distribution Alignment Network (MSSDANet), which introduces novel network structures and loss functions for subdomain-oriented MSDA. …”
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Automatic identification of Dong Son antique glass artifacts using evolving learning by Anh-Khoi Ngo-Ho, Hoang-Bac Bui, Van-Trieu Pham

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Automatic identification of Dong Son antique glass artifacts using evolving learning by Anh-Khoi Ngo-Ho, Hoang-Bac Bui, Van-Trieu Pham

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Detection of Violent Scenes in Cartoon Movies Using a Deep Learning Approach by Noreen Fayyaz Khan, Sareer Ul Amin, Zahoor Jan, Changhui Yan

“…Existing methods have not effectively addressed the issue. In this study, we tackled this challenge by employing a sequential model. …”
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Literatura w grach wideo. Rozeznanie wstępne by Mikołaj Ołownia

“… This article is the first attempt to describe the issue of using literary texts in role-playing video games. …”
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GMO-AC: Gaussian-Based Minority Oversampling With Adaptive Outlier Filtering and Class Overlap Weighting by Seung Jee Yang, Kyungjoon Cha

“…Imbalanced data significantly affects the performance of standard classification models. Data-level approaches primarily use oversampling methods, such as the synthetic minority oversampling technique (SMOTE), to address this problem. …”
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