Revolutionizing Alzheimer’s disease detection with a cutting-edge CAPCBAM deep learning framework by Houmem Slimi, Sabeur Abid, Mounir Sayadi

“…While the integration of deep learning techniques for AD classification is not entirely new, this study introduces CAPCBAM—a framework that extends prior approaches by combining Capsule Networks with a Convolutional Block Attention Module (CBAM). In CAPCBAM, standardized preprocessing of MRI images is followed by feature extraction using Capsule Networks, which preserve spatial hierarchies and capture intricate relationships among image features. …”
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Cross-ViT based benign and malignant classification of pulmonary nodules. by Qinfang Zhu, Liangyan Fei

“…There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmonary nodules, but traditional CNN models focus more on the local features of pulmonary nodules and lack the extraction of global features of pulmonary nodules. …”
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COVID-19 Tweets Classification during Lockdown Period Using Machine Learning Classifiers by Syed Ali Jafar Zaidi, Indranath Chatterjee, Samir Brahim Belhaouari

“…In recent years, COVID-19 has been regarded as the most dangerous pandemic for several countries. On various social media platforms, such as Twitter, Facebook, and Instagram, a variety of rumours, hypes, and news are published. …”
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GaitTriViT and GaitVViT: Transformer-based methods emphasizing spatial or temporal aspects in gait recognition by Hongyun Sheng

“…Moreover, these methods are primarily based on traditional convolutional neural networks (CNNs) due to the dominance of CNNs in computer vision. …”
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Skin Lesion Diagnosis Through Deep Learning and Hybrid Texture Feature Augmentation by Irpan Adiputra Pardosi, Roni Yunis, Arwin Halim

“… Skin cancer is a leading cause of cancer-related deaths globally, with melanoma being the most lethal subtype. Early detection remains critical for improving patient outcomes. …”
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Boosting Skin Cancer Classification: A Multi-Scale Attention and Ensemble Approach with Vision Transformers by Guang Yang, Suhuai Luo, Peter Greer

“…Skin cancer is a significant global health concern, with melanoma being the most dangerous form, responsible for the majority of skin cancer-related deaths. …”
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Trustworthy diagnosis of Electrocardiography signals based on out-of-distribution detection. by Bowen Yu, Yuhong Liu, Xin Wu, Jing Ren, Zhibin Zhao

“…Cardiovascular disease is one of the most dangerous conditions, posing a significant threat to daily health. …”
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Wavelet attention-based implicit multi-granularity super-resolution network by Chen Boying, Shi Jie

“…Abstract Image super-resolution (SR) is a fundamental challenge in the field of computer vision. Recently, Convolutional Neural Network (CNN)-based methods for image SR have achieved significant progress across various SR tasks. …”
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Digital mapping of soil electrical conductivity for paddy field by The Anh Anh, Luu Trong Hieu, Chi Ngon Nguyen

“…This study aims to address this gap by using the common interpolation method —K-Nearest Neighbors (KNN), Inverse Distance Weighting (IDW), Kriging interpolation, and Convolutional Neural Networks (CNN)—to map soil EC over an area of approximately 1.4 hectares. …”
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A fault diagnosis model for pumping units based on small sample electric parameters by Chunhua Yuan, Zhupei Liao, Xiangyu Li

“…Finally, use OMNI-SCALE Convolutional Neural Network (OS-CNN) for fault diagnosis. …”
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Predictive Analysis of Maritime Congestion Using Dynamic Big Data and Multiscale Feature Analysis by Yalin Wu

“…The maritime industry is one of the most crucial sectors in the global economy, facilitating the transportation of goods and commodities across vast distances. …”
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Large-Scale Image Retrieval of Tourist Attractions Based on Multiple Linear Regression Equations by Yinping Song

“…The advantages of feature extraction by a convolutional neural network and the high efficiency of a hash index structure in retrieval are used to solve the shortcomings of traditional methods in terms of accuracy and other aspects in image retrieval. …”
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Deep learning classification integrating embryo images with associated clinical information from ART cycles by Mohamed Salih, Christopher Austin, Krishna Mantravadi, Eva Seow, Sutthipat Jitanantawittaya, Sandeep Reddy, Beverley Vollenhoven, Hamid Rezatofighi, Fabrizzio Horta

“…From the visualisation process we found that female and male age to be the most clinical factors, whilst Trophectoderm to be the most important blastocyst feature. …”
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Precision forecasting for hybrid energy systems using five deep learning algorithms for meteorological parameter prediction by Ceren Ceylan, Zehra Yumurtacı

“…In addition, most of the research uses the same algorithmic solution to all the meteorological parameters without identifying parameter-specific optimization potential, and recent research is verified on actual future time steps instead of historical train-test split. …”
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Multiclass Supervised Learning Approach for SAR-COV2 Severity and Scope Prediction: SC2SSP Framework by Shaik Khasim Saheb, B. Narayanan, T.V. Narayana Rao

“…Although a CT scan is the most common method for diagnosis, CXR is the most frequently utilized since it is more accessible, quicker, and less expensive. …”
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Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature by Bosen Peng, Jiancheng Mu, Feng Xu, Wanyue Guo, Chuhuan Sun, Wei Fan

“…These papers were authored by 87,695 individuals, with Wang Y, Liu Y, and Zhang Y the most prolific authors. Ting DSW was the most co-cited author. …”
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Comparative Analysis of AlexNet, ResNet-50, and VGG-19 Performance for Automated Feature Recognition in Pedestrian Crash Diagrams by Baraah Qawasmeh, Jun-Seok Oh, Valerian Kwigizile

“…Pedestrians, as the most vulnerable road users in traffic crashes, prompt transportation researchers and urban planners to prioritize pedestrian safety due to the elevated risk and growing incidence of injuries and fatalities. …”
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Neurophysiological Approaches to Lie Detection: A Systematic Review by Bewar Neamat Taha, Muhammet Baykara, Talha Burak Alakuş

“…Among classification algorithms, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Convolutional Neural Networks (CNN) were frequently utilized. …”
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Velocity Model Construction and Time-to-Depth Conversion of a Vintage Seismic Reflection Profile for Improving the Constraints on a Subsurface Geological Model: An Example from the... by Aasiya Qadir, Nicolò Chizzini, Mariagiada Maiorana, Andrea Artoni, Luigi Torelli, Attilio Sulli

“…This was followed by the Gaussian convolution operator and a data exclusion filter to improve the accuracy of the velocity model. …”
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GANFlow: A Hybrid Model for SAR Image Target Open-Set Recognition Based on GAN and the Flow-Based Module by Jikai Qin, Jiusheng Han, Zheng Liu, Lei Ran, Rong Xie, Tat-Soon Yeo

“…Most synthetic aperture radar (SAR) automatic target recognition (ATR) methods can achieve good recognition results only under the closed-set assumption. …”
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