RiceLeafClassifier‐v1.0: A Quantized Deep Learning Model for Automated Rice Leaf Disease Detection and Edge Deployment by Oluwaseun O. Martins, Christiaan C. Oosthuizen, Dawood A. Desai

“…Training enhancements included data augmentation, dropout, dynamic learning rate scheduling, and early stopping. …”
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Subdivision of river channel sand micro-scale facies with feature attention spatio-temporal network by Ruipu Zhao, Lili Zeng, Chendong Fu, Xiaoqing Zhao

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Hybrid Multi-Branch Attention–CNN–BiLSTM Forecast Model for Reservoir Capacities of Pumped Storage Hydropower Plant by Yu Gong, Hao Wu, Junhuang Zhou, Yongjun Zhang, Langwen Zhang

“…Pumped storage hydropower plants are important resources for scheduling urban energy storage, which realize the conversion of electric energy through upper and lower reservoir capacities. Dynamic forecasting of reservoir capacities is crucial for scheduling pumped storage and maximizing the economic benefits of pumped storage hydropower plants. …”
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Research on ECG Signal Classification Based on Hybrid Residual Network by Tianyu Qi, He Zhang, Huijun Zhao, Chong Shen, Xiaochen Liu

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A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification by Wei Zhang, Xianlun Tang, Xiaoyuan Dang, Mengzhou Wang

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Detection Algorithm for Air Duct Clamp on Trains Based on RSA-YOLOv10n by WANG Dairong, ZHAO Yuhong, QU Xiaozhang, LIU Yi

“…Firstly, in order to better capture diverse features in images, the Conv convolution is modified to RepConv convolution based on the YOLOv10n model, facilitating adaptive adjustments in the representation ability of the convolution kernel. …”
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Direction-Aware Lightweight Framework for Traditional Mongolian Document Layout Analysis by Chenyang Zhou, Monghjaya Ha, Licheng Wu

“…Our framework introduces three key innovations: a modified MobileNetV3 backbone with asymmetric convolutions for efficient vertical feature extraction, a dynamic feature enhancement module with channel attention for adaptive multi-scale information fusion, and a direction-aware detection head with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mo form="prefix">sin</mo><mi>θ</mi><mo>,</mo><mo form="prefix">cos</mo><mi>θ</mi><mo>)</mo></mrow></semantics></math></inline-formula> vector representation for accurate orientation modeling. …”
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Forecasting Tunnel-Induced Ground Settlement: A Hybrid Deep Learning Approach and Traditional Statistical Techniques With Sensor Data by Syed Mujtaba Hussaine, Linlong Mu, Yimin Lu, Syed Sajid Hussain

“…This study introduces advanced predictive frameworks that incorporate enhancements to both deep learning (DL) models and statistical techniques to handle the intricate, nonlinear, and dynamic characteristics of settlement data. The proposed DL models, Convolutional Long Short-Term Memory (Conv-LSTM2D) and Convolutional Gated Recurrent Unit (Conv-GRU2D), extend traditional LSTM and GRU architectures with 2D convolutional mechanisms to capture complex spatiotemporal dependencies. …”
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Two-Mode Hereditary Model of Solar Dynamo by Evgeny Kazakov, Gleb Vodinchar, Dmitrii Tverdyi

“…This can provide more diverse dynamic modes compared to classical memoryless models. …”
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Combustion Field Prediction and Diagnosis via Spatiotemporal Discrete U-ConvLSTM Model by Xiaodong Huang, Xiaojian Hao, Baowu Pan, Shaogang Chen, Shenxiang Feng, Pan Pei

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Multi-Attribute Data-Driven Flight Departure Delay Prediction for Airport System Using Deep Learning Method by Yujie Yuan, Yantao Wang, Chun Sing Lai

“…The model is based on a 3D convolutional neural network (3D-CNN), graph convolutional network (GCN) and long short-term memory networks (LSTM) model. …”
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Nonlinear time domain and multi-scale frequency domain feature fusion for time series forecasting by Kejiang Xiao, Yefeng Li, Yaning Dong, Wenqi Yang, Binting Yao, Liang Chen

“…At the same time, the framework uses wavelet-based multi-frequency decomposition to clearly divide signals into trend, periodic, and noise components, and enhances feature representation via frequency-domain specific convolutions. Lastly, a gating network dynamically balances temporal and frequency-domain features to achieve cross-domain information integration. …”
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Deep Learning Framework Using Spatial Attention Mechanisms for Adaptable Angle Estimation Across Diverse Array Configurations by Constantinos M. Mylonakis, Pantelis Velanas, Pavlos I. Lazaridis, Panagiotis Sarigiannidis, Sotirios K. Goudos, Zaharias D. Zaharis

“…This paper introduces a novel convolutional neural network (CNN) architecture that combines spatial attention mechanisms with a transfer learning framework to enhance both accuracy and versatility in DoA estimation. …”
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Improved automatic modulation recognition using deep learning with additive attention by Noureddine El-Haryqy, Anass Kharbouche, Hamza Ouamna, Zhour Madini, Younes Zouine

“…This paper proposes ICRNNA, a novel deep learning model that integrates Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (BiLSTM) networks, and an attention mechanism to achieve state-of-the-art performance in AMR tasks. …”
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A novel model for mapping soil organic matter: Integrating temporal and spatial characteristics by Xinle Zhang, Guowei Zhang, Shengqi Zhang, Hongfu Ai, Yongqi Han, Chong Luo, Huanjun Liu

“…In this model, the Convolutional Neural Network (CNN) extracts spatial context features from static variables (e.g., climate and terrain variables), while the Long Short-Term Memory (LSTM) network captures temporal features from dynamic variables (e.g., Sentinel-2 time series from April to October). …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…These factors cause the ship’s movement to be nonlinear, dynamic, and uncertain. Such complex motion can impact the ship’s performance and pose a safety risk. …”
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Classification of Hyperspectral Images of Explosive Fragments Based on Spatial–Spectral Combination by Donge Zhao, Peiyun Yu, Feng Guo, Xuefeng Yang, Yayun Ma, Changli Wang, Kang Li, Wenbo Chu, Bin Zhang

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ResCapsnet: a capsule network with CRAM and BiGRU for sound event detection by Bing Sun, Chenglong Liu, Shuguo Yang, Wenwu Wang, Yiduo Mei

“…Deep learning methods such as convolutional neural networks (CNN) and recurrent neural networks (RNN) have achieved promising performance in SED. …”
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MB-MSTFNet: A Multi-Band Spatio-Temporal Attention Network for EEG Sensor-Based Emotion Recognition by Cheng Fang, Sitong Liu, Bing Gao

“…The model constructs a 3D tensor to encode band–space–time correlations of sensor data, explicitly modeling frequency-domain dynamics and spatial distributions of EEG sensors across brain regions. …”
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Degradation prediction of PEM water electrolyzer under constant and start-stop loads based on CNN-LSTM by Boshi Xu, Wenbiao Ma, Wenyan Wu, Yang Wang, Yang Yang, Jun Li, Xun Zhu, Qiang Liao

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