PassAI: An Explainable Machine Learning Framework for Predicting Soccer Pass Outcomes Using Multimodal Match Data by Ryota Takamido, Jun Ota, Hiroki Nakamoto

“…., coaches and analysts) understand whether pass outcomes depend more on contextual dynamics or individual player traits. In experiments involving 6,349 passes from professional Japanese soccer league games, PassAI outperformed state-of-the-art models—including convolutional neural network-based and graph neural network-based approaches, as well as existing pass prediction models—by more than 5% in accuracy. …”
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Fast segmentation and multiplexing imaging of organelles in live cells by Karl Zhanghao, Meiqi Li, Xingye Chen, Wenhui Liu, Tianling Li, Yiming Wang, Fei Su, Zihan Wu, Chunyan Shan, Jiamin Wu, Yan Zhang, Jingyan Fu, Peng Xi, Dayong Jin

“…Abstract Studying organelles’ interactome at system level requires simultaneous observation of subcellular compartments and tracking their dynamics. Conventional multicolor approaches rely on specific fluorescence labeling, where the number of resolvable colors is far less than the types of organelles. …”
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Deep Learning-Based Sign Language Recognition Using Efficient Multi-Feature Attention Mechanism by Esma Yenisari, Sirma Yavuz

“…Subsequently, dataset-specific contextual features are extracted utilizing distinct network types; spatial dependencies are modeled via Convolutional Neural Networks (CNNs), whereas temporal dynamics are learned through Recurrent Neural Networks (RNNs). …”
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Unraveling trends in schistosomiasis: deep learning insights into national control programs in China by Qing Su, Cici Xi Chen Bauer, Robert Bergquist, Zhiguo Cao, Fenghua Gao, Zhijie Zhang, Yi Hu

“…CONCLUSIONS The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. …”
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Stock Price Forecasting in Iran Stock Market: A Comparative Analysis of Deep-learning Approaches by Faraz Bodaghi, Amin Owhadi, Arash Khalili Nasr, Melody Khadem Sameni

“…Investments in the railway transport industry are vital for boosting other economic areas and have a profound impact on macroeconomic dynamics. Nonetheless, the potential for delayed or uncertain returns may deter investors. …”
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A Spatiotemporal Sequence Prediction Framework Based on Mask Reconstruction: Application to Short-Duration Precipitation Radar Echoes by Zhi Yang, Changzheng Liu, Ping Mei, Lei Wang

“…The former focuses on capturing short-term temporal dynamics, while the latter simultaneously models long-range dependencies across space and time via a self-attention mechanism, thereby avoiding the smoothing effects on high-frequency details that are typical of conventional convolutional or recurrent structures. …”
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Large-scale-aware data augmentation for reduced-order models of high-dimensional flows by Philipp Teutsch, Mohammad Sharifi Ghazijahani, Florian Heyder, Christian Cierpka, Jörg Schumacher, Patrick Mäder

“…Convolutional autoencoders have proven to be an adequate tool to perform reduced-order modeling for high-dimensional nonlinear dynamical systems. …”
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A review on artificial intelligence thermal fluids and the integration of energy conservation with blockchain technology by Abdullah Ayub Khan, Asif Ali Laghari, Syed Azeem Inam, Sajid Ullah, Laila Nadeem

“…The technology provides energy conservation, fluid dynamics, and heat transfer optimisation solutions. …”
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Machine Learning-Based Classification of Sulfide Mineral Spectral Emission in High Temperature Processes by Carlos Toro, Walter Díaz, Gonzalo Reyes, Miguel Peña, Nicolás Caselli, Carla Taramasco, Pablo Ormeño-Arriagada, Eduardo Balladares

“…A one-dimensional convolutional neural network (1D-CNN) was developed and trained on experimentally acquired spectral data, achieving a balanced accuracy score of 99.0% in a test set. …”
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Transfer Learning-Based Accurate Detection of Shrub Crown Boundaries Using UAS Imagery by Jiawei Li, Huihui Zhang, David Barnard

“…The accurate delineation of shrub crown boundaries is critical for ecological monitoring, land management, and understanding vegetation dynamics in fragile ecosystems such as semi-arid shrublands. …”
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Enhancing chronic wound assessment through agreement analysis and tissue segmentation by Ana C. Morgado, Rafaela Carvalho, Ana Filipa Sampaio, Maria J. M. Vasconcelos

“…Abstract Accurate monitoring of chronic wound progression is crucial for assessing healing dynamics. However, the current manual process of tissue segmentation and quantification, which is an indicator of the healing progress, is time-consuming and subject to variability, so automated methods that can effectively monitor wound healing are required. …”
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Understanding and classification of innate immune response through weighted edge representation learning with dual hypergraph transformation by Mallikharjuna Rao Sakhamuri, Shagufta Henna, Leo Creedon, Kevin Meehan, Marion McAfee

“…These results highlight WDHT's effectiveness in capturing peptide-HLA interaction dynamics, providing a robust framework.…”
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Noninvasive Continuous Glucose Monitoring Using Multimodal Near-Infrared, Temperature, and Pressure Signals on the Earlobe by Jongdeog Kim, Bong Kyu Kim, Mi-Ryong Park, Hyoyoung Cho, Chul Huh

“…Continuous glucose data capturing pre- and postprandial variations were analyzed using a 1D convolutional neural network (Conv1D). For three subjects under stable physiological conditions, the model achieved 97.0% Clarke error grid (CEG) A-Zone accuracy and a mean absolute relative difference (MARD) of 5.2%. …”
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Spatiotemporal Super-Resolution of Satellite Sea Surface Salinity Based on a Progressive Transfer Learning-Enhanced Transformer by Zhenyu Liang, Senliang Bao, Weimin Zhang, Huizan Wang, Hengqian Yan, Juan Dai, Peikun Xiao

“…TSR enables higher-resolution satellite monitoring of SSS, contributing to the study of ocean dynamics and climate change.…”
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Research on ocean buoy attitude prediction model based on multi-dimensional feature fusion by Yingjie Liu, Yingjie Liu, Chunlin Ning, Chunlin Ning, Chunlin Ning, Chunlin Ning, Qianran Zhang, Guozheng Yuan, Chao Li

“…This model not only reduces the dimensionality of the original data but also precisely captures the dynamics of ocean elements and their effects on buoy attitudes, leveraging the powerful feature extraction and fusion capabilities of CNN.…”
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Deep Learning and Recurrence Information Analysis for the Automatic Detection of Obstructive Sleep Apnea by Daniele Padovano, Arturo Martinez-Rodrigo, José M. Pastor, José J. Rieta, Raul Alcaraz

“…The present paper addresses this gap by integrating convolutional neural networks (CNNs) with HRV recurrence analysis. …”
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I-AIR: intention-aware travel itinerary recommendation via multi-signal fusion and spatiotemporal constraints by Xiao Cui, Zhihua Wang, Ping Li, Qiang Xu

“…The model combines a multi-head self-attention transformer to capture the sequential and temporal dynamics of user behavior, with a graph convolutional network (GCN) that models complex co-visitation patterns among POIs. …”
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Attention-Enhanced Hybrid Automatic Modulation Classification for Advanced Wireless Communication Systems: A Deep Learning-Transformer Framework by Sam Ansari, Khawla A. Alnajjar, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny, Abir Hussain, Soliman Mahmoud

“…To address these limitations, this paper presents a novel attention-enhanced hybrid AMC framework that synergistically integrates specialized convolutional layers for efficient temporal feature extraction with a compact transformer encoder for global sequence modeling. …”
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Data-driven personalized marketing strategy optimization based on user behavior modeling and predictive analytics: Sustainable market segmentation and targeting. by Bin Sun

“…In this study, we propose a novel framework called DP-GCN (Deterministic Policy Graph Convolutional Network), which integrates multi-level Graph Convolutional Networks (GCNs) with Deep Deterministic Policy Gradient (DDPG) reinforcement learning to model heterogeneous information networks composed of users, products, and search queries. …”
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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…Subsequently, the Temporal Convolutional Network (TCN) was employed to capture temporal dependencies and dynamic variations in the data. …”
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