AlexCapsNet: An Integrated Architecture for Image Classification With Background Noise by Muyi Bao, Nanlin Jin, Ming Xu

“…Capsule networks (CapsNet) are a pioneering architecture that can encode image features into vectors rather than scalars, addressing the limitations of traditional Convolutional Neural Networks (CNNs). …”
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Landslide Susceptibility Prediction Based on a CNN–LSTM–SAM–Attention Hybrid Model by Honggang Wu, Jiabi Niu, Yongqiang Li, Yinsheng Wang, Daohong Qiu

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Incident duration prediction through integration of uncertainty and risk factor evaluation: A San Francisco incidents case study. by Amirreza Salehi, Ardavan Babaei, Majid Khedmati

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Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol by Mauro Podda, Adolfo Pisanu, Gianluca Pellino, Adriano De Simone, Lucio Selvaggi, Valentina Murzi, Eleonora Locci, Matteo Rottoli, Giacomo Calini, Stefano Cardelli, Fausto Catena, Carlo Vallicelli, Raffaele Bova, Gabriele Vigutto, Fabrizio D’Acapito, Giorgio Ercolani, Leonardo Solaini, Alan Biloslavo, Paola Germani, Camilla Colutta, Savino Occhionorelli, Domenico Lacavalla, Maria Grazia Sibilla, Stefano Olmi, Matteo Uccelli, Alberto Oldani, Alessio Giordano, Tommaso Guagni, Davina Perini, Francesco Pata, Bruno Nardo, Daniele Paglione, Giusi Franco, Matteo Donadon, Marcello Di Martino, Dario Bruzzese, Daniela Pacella

“…The ML model will utilise convolutional neural networks (CNN) for feature extraction and risk prediction. …”
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Polarization of road target detection under complex weather conditions by Feng Huang, Junlong Zheng, Xiancai Liu, Ying Shen, Jinsheng Chen

“…This module integrates channel-wise global self-attention and small kernel convolution to adaptively adjust the polarization enhancement method using dynamically extracted global and local polarization feature information. A multi-scale detection network is also designed to fully extract and fuse multi-scale feature information from receptive fields, channels, and spaces in different dimensions. …”
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Bearing fault diagnosis method based on SAVMD and CNN by SONG ChunSheng, LIANG YaRu, LU NiFang, DU Gang, JIA Bo

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Graphical representation of landscape heterogeneity identification through unsupervised acoustic analysis by Maria J. Guerrero, Camilo Sánchez‐Giraldo, César A. Uribe, Víctor M. Martínez‐Arias, Claudia Isaza

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Diagnosis of depression based on facial multimodal data by Nani Jin, Renjia Ye, Peng Li

“…We use spatiotemporal attention module to enhance the extraction of visual features and combine the Graph Convolutional Network (GCN) and the Long and Short Term Memory (LSTM) to analyze the audio features. …”
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An Adaptive Convolutional Neural Network With Spatio-Temporal Attention and Dynamic Pathways (ACNN-STADP) for Robust EEG-Based Motor Imagery Classification by Aaqib Raza, Mohd Zuki Yusoff

“…The proposed model integrates a Dynamic Pathway Convolution Network (DPCN) for adaptive feature extraction, incorporating a Dynamic Gating Controller (DGC) and Dynamic Adaptive Spatio-Temporal (DAST) blocks to efficiently capture multi-scale spatial and temporal dependencies. …”
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Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms by Manal Abdullah Alohali, Sultan Alahmari, Mohammed Aljebreen, Mashael M. Asiri, Achraf Ben Miled, Sami Saad Albouq, Othman Alrusaini, Ali Alqazzaz

“…Abstract Internet of Vehicles (IoV) is a multi-node network which switches data in an open and wireless environment. …”
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TRI-POSE-Net: Adaptive 3D human pose estimation through selective kernel networks and self-supervision with trifocal tensors. by Nabeel Ahmed Khan, Aisha Ahmed Alarfaj, Ebtisam Abdullah Alabdulqader, Nuha Zamzami, Muhammad Umer, Nisreen Innab, Tai-Hoon Kim

“…The proposed technique, which is based on ResNet-50 and includes integrated Selective Kernel Network (SKNet) blocks, has proven to be efficient for feature extraction customised specifically to pose estimation scenarios. …”
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MPFM-VC: A Voice Conversion Algorithm Based on Multi-Dimensional Perception Flow Matching by Yanze Wang, Xuming Han, Shuai Lv, Ting Zhou, Yali Chu

“…Unlike traditional approaches that directly generate waveform outputs, MPFM-VC models the evolutionary trajectory of mel spectrograms with a flow-matching framework and incorporates a multi-dimensional feature perception network to enhance the stability and quality of speech synthesis. …”
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An Insight on the Timely Diagnosis of Diabetic Retinopathy Using Traditional and AI-Driven Approaches by Malaika Asif, Fasih Ur Rehman, Zoya Rashid, Altaf Hussain, Alina Mirza, Waqar Shahid Qureshi

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Morphological-Priors-Guided Network With Semantic Booster and Scalable Bins Module for Height Estimation From Single-View Remote Sensing Images by Tao Zhang, Furong Shi, Yuanping Zhu

“…First, considering the semantic morphological priors, we propose to explicitly enhance the 3-D visual cues (e.g., co-occurrence relationship between shadow buildings and shadow trees) and simultaneously design a semantic booster composed of a two-stream network with a multilevel cross-stream attention fusion mechanism to facilitate the 3-D feature learning for monocular height estimation. …”
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Effect of Different Temperature and Humidity Storage Conditions on the Quality of Fresh Macadamia Nuts and the Construction of A Backpropagation Neural Network Prediction Model by Jiarong FU, Shangxuan MA, Yuexue YANG, Wenting XU, Xiuhua LAN, Yuanmiao WEI, Kechang HUANG, Xiyong HE, Gangjun GUO

“…In addition, the cracking and mold rates of pericarps, acid value, peroxide value, iodine value, total phenol content, and total sugar content were evaluated. A quality prediction model for the short-term storage of fresh macadamia nuts was developed using a backpropagation (BP) neural network, and its predictive capability was evaluated using a test set. …”
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Developing a novel hybrid model based on GRU deep neural network and Whale optimization algorithm for precise forecasting of river’s streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Farshad Ahmadi, Rasoul Mirabbasi, Ali Torabi Haghighi

“…Abstract Streamflow contemplates a fundamental criterion to evaluate the impact of human activities and climate changes on the hydrological cycle. …”
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Resting‐State Functional Connectivity of Sensorimotor and Default Mode Networks and Lower Limb Performance in Chronic Stroke: A Cross‐Sectional Study by Svetlana Pundik, Margaret M. Skelly, Jessica P. McCabe, Ahlam I. Salameh, Trenley Anderson, Kelsey Rose Duncan, Terri Hisel, Sarah J. A. Carr

“…Our objective was to evaluate the relationship between lower limb performance and resting‐state functional connectivity (rsFC) of large‐scale brain networks for individuals with chronic motor deficits (> 6 months) after stroke. …”
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Evaluating Time Series Models for Monthly Rainfall Forecasting in Arid Regions: Insights from Tamanghasset (1953–2021), Southern Algeria by Ballah Abderrahmane, Morad Chahid, Mourad Aqnouy, Adam M. Milewski, Benaabidate Lahcen

“…This is particularly important in arid regions like Tamanghasset, where precipitation is the primary driver of agricultural viability and water resource management. This study evaluates the performance of several time series models for monthly rainfall prediction, including the autoregressive integrated moving average (ARIMA), Exponential Smoothing State Space Model (ETS), Seasonal and Trend decomposition using Loess with ETS (STL-ETS), Trigonometric Box–Cox transform with ARMA errors, Trend and Seasonal components (TBATS), and neural network autoregressive (NNAR) models. …”
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A comprehensive analysis of digital inclusive finance’s influence on high quality enterprise development through fixed effects and deep learning frameworks by Dedai Wei, Zimo Wang, Hanfu Kang, Xinye Sha, Yiran Xie, Anqi Dai, Kaichen Ouyang

“…Then, based on the results of these tests, we selected deep learning features and combined Kolmogorov–Arnold Neural Network (KAN), Graph Neural Network (GNN) models with classic time series deep learning models (Transformer, LSTM, BiLSTM, GRU) to capture the latent nonlinear features in the data for prediction. …”
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Study on a Traditional Chinese Medicine constitution recognition model using tongue image characteristics and deep learning: a prospective dual-center investigation by Yongyue Liu, Linmiao Fan, Mei Zhao, Dongshen Wei, Menglan Zhao, Yihang Dong, Xiaoqing Zhang

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