Deep Fusion of Skeleton Spatial–Temporal and Dynamic Information for Action Recognition by Song Gao, Dingzhuo Zhang, Zhaoming Tang, Hongyan Wang

“…Furthermore, physical structure constraints of the human body were considered to enhance class differences. Additionally, the speed information for each joint was estimated and encoded as a color texture map to achieve the skeleton motion feature descriptor. …”
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Research and Application of Complex Lithology Identification Method Based on CNN-GRU by ZHANG Xiaofeng, PANG Chunyang, HU Rui, ZHU Yunfeng, LI Hongxing

“…This study integrates convolutional neural networks with gated recurrent units (CNN-GRU) and selects six logging parameters, including sonic time difference, natural potential, natural gamma, density, and shallow and deep lateral resistivity, to train sample wells in the Hailar basin. …”
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Mapping Coastal Soil Salinity and Vegetation Dynamics Using Sentinel-1 and Sentinel-2 Data Fusion With Machine Learning Techniques by Wen Liu, Tiezhu Shi, Zhinian Zhao, Chao Yang

“…The analysis has been conducted for a coastal region in China, where derived features, such as normalized difference vegetation index (NDVI), salinity indices, and SAR-based soil moisture proxies, have been used as inputs to the CNN model. …”
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Prediction of State-of-Health and Remaining-Useful-Life of Battery Based on Hybrid Neural Network Model by Le Thi Minh Lien, Vu Quoc Anh, Nguyen Duc Tuyen, Goro Fujita

“…Firstly, capacity and different health indicators with high correlation extracted from the battery’s charging and discharging characteristics are considered inputs. …”
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Deep Learning-Based Surface Temperature Prediction for a Porous Radiant Burner Using Thermocouple-Calibrated Thermal Infrared Images by Hao-Yu Hsieh, Shenqyang Shy, Wei-Wun Wang, Yung-Chien Chou

“…The temperature measurement range and the emissivity of the IR camcorder are set at 300-2000°C and 0.95, respectively, having an average temperature of about 40°C difference/uncertainty as compared to that measured by the thermocouples. …”
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A hybrid deep learning-based approach for optimal genotype by environment selection by Zahra Khalilzadeh, Motahareh Kashanian, Saeed Khaki, Lizhi Wang

“…The ability to accurately predict the yields of different crop genotypes in response to weather variability is crucial for developing climate resilient crop cultivars. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…Even with medium-level noise (<inline-formula> <tex-math notation="LaTeX">$\sigma \approx 0.05$ </tex-math></inline-formula>), the model maintains 77% of its R2 value, and when applied to strawberry price prediction using the dataset published by the United States Department of Agriculture Economic Research Service (USDA ERS)&#x2014;a product with significantly different market characteristics&#x2014;it achieves an R2 value of 0.7499 without any retraining, demonstrating strong adaptability to different data distributions. …”
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TCN-GRU Based on Attention Mechanism for Solar Irradiance Prediction by Zhi Rao, Zaimin Yang, Xiongping Yang, Jiaming Li, Wenchuan Meng, Zhichu Wei

“…Considering the time series nature of the GHI and monitoring sites dispersed over different latitudes, longitudes, and altitudes, this study proposes a model combining deep neural networks and deep convolutional neural networks for the multi-step prediction of GHI. …”
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A brain tumor segmentation enhancement in MRI images using U-Net and transfer learning by Amin Pourmahboubi, Nazanin Arsalani Saeed, Hamed Tabrizchi

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Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification by Zengshu Shi, Yiman Du, Xinwen Yao

“…It has a good anti‐noise performance under different convolution kernels and SNRs. When the sample distribution is unbalanced, the performance indexes obtained by the proposed model are the best.…”
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Enhancing Landmark Point Detection in <i>Eriocheir Sinensis</i> Carapace with Differentiable End-to-End Networks by Chong Wu, Shuxian Wang, Shengmao Zhang, Hanfeng Zheng, Wei Wang, Shenglong Yang

“…A 37-point localization framework was developed for the carapace, with the dataset augmented through random distortions, rotations, and occlusions to enhance generalization capability. Three types of convolutional neural network models were used to compare detection accuracy, generalization ability, and model power consumption, with different loss functions compared. …”
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Detecting performance difficulty of learners in colonoscopy: Evidence from eye-tracking by Xin Liu, Bin Zheng, Xiaoqin Duan, Wenjing He, Yuandong Li, Jinyu Zhao, Chen Zhao, Lin Wang

“…Basic human eye gaze and pupil characteristics were learned and verified by the deep convolutional generative adversarial networks (DCGANs); the generated data were fed to the Long Short-Term Memory (LSTM) networks with three different data feeding strategies to classify MNLs from the entire colonoscopic procedure. …”
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Influence of land cover on noise simulation output – A case study in Malmö, Sweden by Pantazatou Karolina, Mattisson Kristoffer, Olsson Per-Ola, Telldén Erik, Kettisen Anders, Hosseinvash Azari Soraya, Liu Wenjing, Harrie Lars

“…This study examines how different LC datasets influence simulated environmental noise levels of road traffic using Nord2000 in an urban area of 1 km2 in southern Sweden. …”
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An islanding detection method for grid-connect inverter based on parameter optimized variational mode decomposition and deep learning by Yan Xia, Yan Xia, Yuli Lv, Feihong Yu, Yiqiang Yang, Yili Yang, Wei Li, Ke Li

“…Simulation results indicate that the proposed method can effectively differentiate the islanding state under different working conditions with a testing accuracy level of 100% within a maximal detection time of 46.402 ms. …”
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Multi-Modal AI for Multi-Label Retinal Disease Prediction Using OCT and Fundus Images: A Hybrid Approach by Amina Zedadra, Mahmoud Yassine Salah-Salah, Ouarda Zedadra, Antonio Guerrieri

“…These results confirm the robustness, reliability, and generalization capability of the proposed approach across different imaging modalities.…”
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Text Analysis of Digital Commentary on Ice and Snow Tourism Based on Artificial Intelligence and Long Short-Term Memory Neural Network by Qi Zhuang, Zhengjie Chu, Jun Li

“…In particular, the model shows superior performance in the sentiment classification of long review texts, effectively enhancing the accuracy and granularity of sentiment recognition through dynamic convolution and the self-attention mechanism. Moreover, the model distinguishes sentiment tendencies across different user groups regarding their experiences in ice and snow tourism. …”
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Advancements in Efficient Underwater Image Restoration Using ETransMapNet for Enhanced Dehazing by C. P. Indumathi, Haya Mesfer Alshahrani, N. A. Natraj, C. H. Sarada Devi

“…ETransMapNet extracts features using three convolution kernels of different sizes (3 × 3, 5 × 5, and 7 × 7). …”
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AI-Driven Innovation Using Multimodal and Personalized Adaptive Education for Students With Special Needs by Nesren Farhah, Muhammad Adnan, Ahmed Abdullah Alqarni, M. Irfan Uddin, Theyazn H. H. Aldhyani

“…These findings suggest that more advanced and intelligent neural networks can improve how students with different learning abilities consume content and, consequently, provide better educational answers and solutions to the market. …”
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SGCL-LncLoc: An Interpretable Deep Learning Model for Improving lncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning by Min Li, Baoying Zhao, Yiming Li, Pingjian Ding, Rui Yin, Shichao Kan, Min Zeng

“…Then, SGCL-LncLoc applies graph convolutional networks to learn the comprehensive graph representation. …”
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Short-term train arrival delay prediction: a data-driven approach by Qingyun Fu, Shuxin Ding, Tao Zhang, Rongsheng Wang, Ping Hu, Cunlai Pu

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