Comparative Analysis of Advanced Models for Predicting Housing Prices: A Review by Inmaculada Moreno-Foronda, María-Teresa Sánchez-Martínez, Montserrat Pareja-Eastaway

“…These attributes include the property’s location, its internal features, and the distance from the property to city centers.…”
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Gradient cement pastes with efficient energy dissipation and electromagnetic wave absorption by Yihao Xiao, Yajing Miao, Xin Zhang, Yahui Xue

“…This gradient design enhances toughness and impact resistance by optimizing microstructural features and interfacial interactions, which facilitate efficient load transfer and stress delocalization. …”
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Personalized Recommendation System of E-Commerce in the Digital Economy Era: Enhancing Social Connections with Graph Attention Networks by Yuan He, Yonghong Du, Xiaofei Pu

“…Additionally, the model incorporates graph contrastive learning to extract universal features of users and items, further mitigating the sparse data challenge. …”
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Soil Organic Carbon Monitoring and Modelling via Machine Learning Methods Using Soil and Remote Sensing Data by Dimitrios Triantakonstantis, Andreas Karakostas

“…The accurate monitoring and modelling of SOC are essential for assessing soil fertility, facilitating sustainable land management, and mitigating climate change. (2) Methods: This research paper explores the integration of machine learning (ML) approaches with soil, terrain and remotely sensed data to enhance SOC estimation. …”
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Rapid eigenpatch utility classifier for image denoising by Michael A. J. Mitchell, Stefano Sanvito, Lewys Jones

“…This classification-only approach to DNN integration represents a significant advance by mitigating the risk of DNN overreach while maintaining denoising effectiveness. …”
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The RTM Event Database for Understanding Natural Hazards in Mountainous Regions: The Example of the Isere Department (France) by Alix Bisquert, Robin Mainieri, Simon Carladous, Yannick Robert, Florie Giacona, Pierre Verry, Nicolas Eckert

“…Databases of natural hazards play a crucial role for assessing related risks and in mitigating their impacts on the environment. In the mountainous regions of France, potentially destructive events are both numerous and diverse, however, only a limited number of databases containing information on past occurrences exist. …”
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A generative model-based coevolutionary training framework for noise-tolerant softsensors in wastewater treatment processes by Yu Peng, Erchao Li

“…To tackle this issue, this study introduces a coevolutionary training framework based on generative models to mitigate the impact of noise corruption. The framework employs a denoising variational autoencoder to extract global and local features from auxiliary data, enhancing population distribution and constructing a deep nonlinear representation to counter noise effects. …”
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Predicting Epileptic Seizures Using EfficientNet-B0 and SVMs: A Deep Learning Methodology for EEG Analysis by Yousif A. Saadoon, Mohamad Khalil, Dalia Battikh

“…The framework leverages normalized Short-Time Fourier Transform (STFT) and channel correlation features extracted from EEG signals to capture both spectral and spatial information. …”
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Enhancing Anti-Money Laundering Frameworks: An Application of Graph Neural Networks in Cryptocurrency Transaction Classification by Stefano Ferretti, Gabriele D'Angelo, Vittorio Ghini

“…These efforts play a crucial role in promoting societal welfare by mitigating the impact of criminal activities. This paper explores the application of Graph Neural Networks (GNNs) for classifying Bitcoin transactions. …”
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Evaluation of polarization modes and spatial resolution of PALSAR-2 for canal detection accuracy in Indonesia peatlands by Muhammad Haidar, Wataru Takeuchi

“…Drainage canal inventories are vital for understanding peatland hydrology and mitigating CO2 emissions from drained peatlands. This study presents a deep learning approach to develop an ensemble classifier for canal segmentation using PALSAR-2, incorporating hyperparameter tuning, multi-polarization configurations, and input resolution assessment. …”
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A Secure Cooperative Adaptive Cruise Control Design with Unknown Leader Dynamics Under False Data Injection Attacks by Parisa Ansari Bonab, Arman Sargolzaei

“…One of the most promising features of CAVs is cooperative adaptive cruise control (CACC). …”
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Application of Electrical Resistivity Tomography and Induced Polarization for Pre-Construction Site Assessment in Ipoh, Perak, Malaysia by Musty Sadiq Bukar, Bery Andy Anderson

“…The research aims to determine the subsurface resistivity distribution and identify geological features critical for construction planning. By employing ERT and IP techniques along 2 profiles, L1 and L2 at the site, the study evaluates variations in soil and rock characteristics and potential instability zones. …”
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Research into the Application of ResNet in Soil: A Review by Wenjie Wu, Lijuan Huo, Gaiqiang Yang, Xin Liu, Hongxia Li

“…ResNet outperforms traditional methods by effectively mitigating the vanishing gradient problem, enabling deeper network training, enhancing feature extraction, and improving accuracy in complex pattern recognition tasks. …”
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Multi scale supervised entropy weighted binary pattern for texture classification by Xiaochun Xu, Bin Li

“…The complexity of imaging environments, variations in acquisition angles and distances, and differences in resolution make representing multi-scale texture features a core challenge in texture analysis. However, most existing multi-scale methods are overly complex and redundant, often neglecting the correlation of texture features across different scales. …”
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Kenyan sign language word-based pose datasetZenodo by Ezekiel Maina, Lilian Wanzare, James Obuhuma, Mildred Ayere, Maurine Kang'ahi, Joel Okutoyi

“…Stickman representations abstract human features, mitigating ethical concerns associated with traditional video datasets and aligning with privacy-preserving practices. …”
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DiffTST: Diff Transformer for Multivariate Time Series Forecast by Song Yang, Wenyong Han, Yaping Wan, Tao Zhu, Zhiming Liu, Shuangjian Li

“…To mitigate this issue, our study introduces DiffTST, which employs a Differential Transformer to enhance the model’s focus on relevant context within the time series, thereby mitigating the influence of noise on forecasting accuracy. …”
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Optimisation of the adaptive neuro-fuzzy inference system for adjusting low-cost sensors PM concentrations by Martina Casari, Piotr A. Kowalski, Laura Po

“…Notably, incorporating only PM2.5, relative humidity and temperature as features yields optimal performance while mitigating overfitting issues. …”
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CSNet: A Remote Sensing Image Semantic Segmentation Network Based on Coordinate Attention and Skip Connections by Jiahao Li, Hongguo Zhang, Liang Chen, Binbin He, Huaixin Chen

“…Furthermore, skip connections are introduced between the encoder and decoder to directly transfer low-level features to the decoder. This promotes the fusion of semantic information at different levels, enhances the recovery of fine-grained details, and optimizes the gradient flow during training, effectively mitigating the vanishing gradient problem and improving training efficiency. …”
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Enhancing Underwater Video from Consecutive Frames While Preserving Temporal Consistency by Kai Hu, Yuancheng Meng, Zichen Liao, Lei Tang, Xiaoling Ye

“…In addition, to address the limitations of traditional U-Net models in handling complex multiscale feature fusion, this study proposes a novel underwater feature fusion module. …”
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Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models by Vasundhara Acharya, Bülent Yener, Gillian Beamer

“…The teacher model demonstrated decent performance due to its higher complexity and ability to use cell graph structures and features. Its logits provided rich information and regularization to students, mitigating the risk of overfitting the training distribution. …”
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