Recognition and classification techniques of marine mammal calls based on LSTM and expanded causal convolution by Wanlu Cheng, Wanlu Cheng, Hao Chen, Jiaming Jiang, Jiaming Jiang, Shuang Li, Shuang Li, Jingjing Wang, Jingjing Wang, Yanping Zhou

“…To address these challenges, we propose a hybrid architecture combining a time-attention Long Short-Term Memory (LSTM) network and a multi-scale dilated causal convolutional network. …”
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Research on Grouting Dynamic Monitoring Based on Borehole–Tunnel Joint Resistivity Method by Cheng Wang, Lei Zhou, Liangjun Yan, Bofan Li

“…The technology can provide reliable grouting evaluation for mine disaster control engineering.…”
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Study on Photovoltaic Plant Site Selection Models Based on Geographic and Environmental Features by RAO Zhi, YANG Zaimin, YANG Xiongping, LI Jiaming, YANG Ping, WEI Zhichu

“…[Conclusions] The TCN-Informer model exhibited significant advantages in terms of accuracy and robustness for GHI prediction， enabling a more effective capture of temporal variation patterns in solar irradiance. It has a strong engineering application potential and provides solid data support for solar resource evaluation and photovoltaic site planning.…”
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Hybrid Deep Learning Architecture with Adaptive Feature Fusion for Multi-Stage Alzheimer’s Disease Classification by Ahmad Muhammad, Qi Jin, Osman Elwasila, Yonis Gulzar

“…Traditional convolutional neural networks (CNNs) and deep learning models often fail to effectively integrate localized brain changes with global connectivity patterns, limiting their efficacy in Alzheimer’s disease (AD) classification. …”
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Variational Methods in Optical Quantum Machine Learning by Marco Simonetti, Damiano Perri, Osvaldo Gervasi

“…As a case study, we considered the binary classification of points belonging to a certain geometric pattern (the Two-Moons Classification problem) on a plane. …”
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Personal Information Sharing Behavior Using Social Media by Ashraf Sharif, Shafiq Ur Rehman, Khalid Mahmood

“…This study explores personal information sharing behavior publication patterns and trends on social media from 2007-2024 with an aim to highlight the annual growth of personal information sharing behavior (PISB) on social media platforms, key patterns in the PISB literature in terms of frequently cited authors, countries, institutions, sources, highly cited papers, collaboration and authorship patterns, thematic evolution, keyword and key factor analysis (such as countries, sources, and keywords). …”
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Application of a KAN-LSTM Fusion Model for Stress Prediction in Large-Diameter Pipelines by Zechao Li, Shiwei Qin

“…The model is trained and validated using actual pipeline monitoring data, ensuring that it accurately captures both the temporal dependencies and nonlinear stress patterns inherent in such systems. By modifying the fully connected layer of the original LSTM model, we develop a novel LSTM-KAN model and evaluate its performance through comprehensive predictive analysis. …”
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Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon by Abhishu Oza, Dhaval K. Patel, Bryan J. Ranger

“…In this paper, we propose Fusion ConvLSTM-Net, a novel fusion encoder-decoder architecture that combines both spatial and temporal features to extend the load forecast to a full 24 hour period. We evaluated the model against several benchmark neural network models by: 1) testing different forecast window sizes ranging from 1.5 to 24 hours, 2) assessing model performance across multiple households, and 3) performing large-scale forecasting by aggregating predictions from 100 households. …”
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RQPool: A Novel Multi-Branch Graph-Level Anomaly Detection by Aaron Alex Philip, Ziad Kobti

“… Anomaly Detection (AD) is crucial across various domains, as it identifies irregularities or unusual patterns that, if quickly addressed, can prevent financial and data losses, protect health, and prevent disasters. …”
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Deep Temporal and Structural Embeddings for Robust Unsupervised Anomaly Detection in Dynamic Graphs by Samir Abdaljalil, Hasan Kurban, Rachad Atat, Erchin Serpedin, Khalid Qaraqe

“…Our method successfully captures temporal patterns, making it robust against subtle anomalies and structural changes. …”
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Censoring Sensitivity Analysis for Benchmarking Survival Machine Learning Methods by János Báskay, Tamás Mezei, Péter Banczerowski, Anna Horváth, Tamás Joó, Péter Pollner

“…Five models were evaluated: Cox proportional hazards, survival tree, random survival forest, gradient-boosted survival analysis, and mixture density networks. …”
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Histopathological-based brain tumor grading using 2D-3D multi-modal CNN-transformer combined with stacking classifiers by Naira Elazab, Fahmi Khalifa, Wael Gab Allah, Mohammed Elmogy

“…Our pipeline uses complementary feature extraction techniques to capture domain-specific knowledge related to brain tumor morphology, such as texture and intensity patterns. An efficient method of learning hierarchical patterns within the tissue is the 2D-3D hybrid convolution neural network (CNN), which extracts contextual and spatial features. …”
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Enhancing microgrid forecasting accuracy with SAQ-MTCLSTM: A self-adjusting quantized multi-task ConvLSTM for optimized solar power and load demand predictions by Ehtisham Lodhi, Nadia Dahmani, Syed Muhammad Salman Bukhari, Sujan Gyawali, Sanjog Thapa, Lin Qiu, Muhammad Hamza Zafar, Naureen Akhtar

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Hydroelectric Unit Fault Diagnosis Based on Modified Fractional Hierarchical Fluctuation Dispersion Entropy and AdaBoost-SCN by Xing Xiong, Zhexi Xu, Rende Lu, Yisheng Li, Bingyan Li, Fengjiao Wu, Bin Wang

“…Then, a novel method for evaluating the complexity of time-series signals, called MFHFDE, is presented. …”
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Impact of Normalization Techniques on Synthetic Load Profile Generation Using Deep Generative Models by Luis H. T. Bandoria, Walquiria N. Silva, Madson C. De Almeida

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Deep-m6Am: a deep learning model for identifying N6, 2′-O-Dimethyladenosine (m6Am) sites using hybrid features by Islam Uddin, Salman A. AlQahtani, Sumaiya Noor, Salman Khan

“…Finally, a multilayer deep neural network (DNN) is used as a classification algorithm for identifying m6Am sites. …”
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A Novel Optimization Approach for Revolutionizing Architectural Design in Chinese Cultural Heritage by Xueyong Li, Xiaoqing Yang

“…Using this approach, machine learning models may be taught to see patterns, fix errors, and make wise predictions under different conditions.   …”
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Interpretable Deep Learning for Diabetic Retinopathy: A Comparative Study of CNN, ViT, and Hybrid Architectures by Weijie Zhang, Veronika Belcheva, Tatiana Ermakova

“…Deep learning models have been widely used for automated DR classification, with Convolutional Neural Networks (CNNs) being the most established approach. …”
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IoT in Smart Urban Planning: A Comprehensive Review of Applications, Developments, and Engineering Perspectives by Ahmed A. Zakaria, Tasneem Amr, Amany A. Ragheb

“…It also analyzes smart city investment patterns, highlighting the growth of IoT-driven infrastructure and service models. …”
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Deep Learning Innovations: ResNet Applied to SAR and Sentinel-2 Imagery by Giuliana Bilotta, Luigi Bibbò, Giuseppe M. Meduri, Emanuela Genovese, Vincenzo Barrile

“…A test dataset derived from Sentinel-2 raster images is utilised to evaluate the effectiveness of the neural network (NN). …”
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