Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Karima Nifa, Bouchra Bargam, Abdelghani Chehbouni

“…Study focus: The research integrates remote sensing data, particularly the Normalized-Difference Snow Index (NDSI) from the MODIS Sensor, with machine learning (ML) and deep learning (DL) models to predict daily snow depth (DSD) at a local scale. …”
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Tactile Augmentation of Material Classification via Imperceptible On‐Skin Triboelectricity Collection by Junting Huang, Stanley Gong Sheng Ka, Haydn Cheong, Yaru Zhang, Daping Chu, Sohini Kar‐Narayan, Wenyu Wang, Yan Yan Shery Huang

“…A machine learning technique is developed to process the triboelectric signals, enabling the classification of six different materials with a prediction accuracy of ≈95%. …”
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A Motion‐Sensing Integrated Soft Robot with Triboelectric Nanogenerator for Pipeline Inspection by Rui Chen, Huigang Wang, Haoji Wang, Huijiang Wang, Li Bai, Xinpei Ai, Lifu Liu, Zhihao Hu, Zean Yuan

“…The T‐TENG‐based sensory system outputs distinct voltage signals upon exposed to different material and structural conditions, for which a 1D‐convolutional neutral network algorithm is exposed to process with the sequential signals. …”
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Temporal–Spatial Partial Differential Equation Modeling of Land Cover Dynamics via Satellite Image Time Series and Sparse Regression by Ming Kang, Zheng Zhang, Zhitao Zhao, Keli Shi, Junfang Zhao, Ping Tang

“…Using MODIS and Planet satellite data, we demonstrate the effectiveness of the TS-PDE method in predicting the value of the normalized difference vegetation index (NDVI) and interpreting the physical significance of the derived equations. …”
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Automated Foveal Avascular Zone Segmentation in Optical Coherence Tomography Angiography Across Multiple Eye Diseases Using Knowledge Distillation by Peter Racioppo, Aya Alhasany, Nhuan Vu Pham, Ziyuan Wang, Giulia Corradetti, Gary Mikaelian, Yannis M. Paulus, SriniVas R. Sadda, Zhihong Hu

“…Although several automated FAZ detection and segmentation algorithms have been developed for use with OCTA, their performance can vary significantly due to differences in data accessibility of OCTA in different retinal pathologies, and differences in image quality in different subjects and/or different OCTA devices. …”
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Structural Similarity-Guided Siamese U-Net Model for Detecting Changes in Snow Water Equivalent by Karim Malik, Colin Robertson

“…Aggregating snow measurements, however, can magnify the modifiable aerial unit problem, resulting in differing snow trends at different temporal resolutions. …”
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MSTCNet: Toward Generalization Improving for Multiframe Infrared Small Target Detection by Ruining Cui, Na Li, Junfu Liu, Huijie Zhao

“…These changes lead to differences between the data distribution in actual application scenarios and the training scenarios. …”
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MEViT: Generalization of Deepfake Detection With Meta-Learning EfficientNet Vision Transformer by Van-Nhan Tran, Hoanh-Su Le, Piljoo Choi, Suk-Hwan Lee, Ki-Ryong Kwon

“…With the rapid advances in deep generative models, the accessibility and sophistication of such manipulation technologies are increasing, making it more challenging to detect fake content. Different facial forgery techniques result in complex data distributions, and most existing deepfake detection approaches rely on convolutional neural networks (CNNs) that treat the task as a binary classification problem. …”
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TADNet: A Time and Attention-Based Point Cloud Denoising Network for Autonomous Driving in Adverse Weather by Y. Zhang, H. Huang, X. Yan, Y. Liang, Y. Li, J. Yang

“…The experimental results show that the denoising effect of TADNet in three kinds of bad weather, namely rain, snow and fog, is better than other methods, which can remove different kinds of noise with different intensities and retain the environmental features, and has the best performance of IoU and MIoU in all kinds of weather conditions.…”
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GLAI-Net: Global–Local Awareness Integrated Network for Semantic Change Detection in Remote Sensing Images by Qing Ding, Fengyan Wang, Mingchang Wang, Ying Zhang, Gui Cheng

“…Meanwhile, we propose multi-scale feature fusion (MSFF) modules in GLAI-Net to enhance the focus of detail features on changed objects with different sizes. Between the classification and change detection decoding branches, we propose semantic change response (SCR) modules in GLAI-Net that fully utilize the correlation between different tasks to improve the consistency and accuracy of detection results. …”
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A systematic review on the associations between built environment and mental health among older people by Yongkang Chen, Lizhen Xu, Xiangfen Cui, Haoran Yang, Haoran Yang, Yiling Liu, Xin Gao, Jianhong Huang

“…Furthermore, a higher proportion of green spaces, improved facility accessibility, and shorter travel times and distances to destinations are positively linked with better MH of older adults.DiscussionWhile these associations are becoming increasingly evident, research on the effects of density, diversity, and design elements in relation to older adults’ MH remains limited and may varied significantly across different regions. Future research should focus on designing quasi-natural experimental studies to enhance our understanding of the convoluted and elaborate relationship between the BE and MH.…”
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Fault Diagnosis Based On Improved Information Entropy And 1dcnn For Marine Turbocharger Rotor With Variable Speed by Hu Lei, Hu Haoran, Hu Nao, Liu Luyuan, Dong Fei, Yang Jianguo, Zhong Jiahong

“…Faults in the turbocharger rotor at the different speeds are classified using a one-dimensional convolutional neural network (1DCNN), and the arithmetic ability of the diagnostic algorithm is evaluated. …”
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Soil moisture retrieval over agricultural region through machine learning and sentinel 1 observations by Deepanshu Lakra, Deepanshu Lakra, Shobhit Pipil, Prashant K. Srivastava, Suraj Kumar Singh, Manika Gupta, Rajendra Prasad

“…The backscattering coefficients were taken as the input variables and SM as the output variable for the training and testing of different models. The performance analysis of RMSE, R-squared, and correlation coefficients revealed that the Random Forest (RF) and Convolutional Neural Network (CNN) models demonstrated superior performance for SM estimation over the wheat field. …”
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A Study of Mixed Non-Motorized Traffic Flow Characteristics and Capacity Based on Multi-Source Video Data by Guobin Gu, Xin Sun, Benxiao Lou, Xiang Wang, Bingheng Yang, Jianqiu Chen, Dan Zhou, Shiqian Huang, Qingwei Hu, Chun Bao

“…The density–flow model calculates a pure EV capacity of 2349–2897 bikes/(h·m) and a pure bicycle capacity of 1753–2173 bikes/(h·m). The minimal difference between these estimates validates the effectiveness of the proposed model. …”
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A Novel Audio Copy Move Forgery Detection Method With Classification of Graph-Based Representations by Beste Ustubioglu, Gul Tahaoglu, Arda Ustubioglu, Guzin Ulutas, Muhammed Kilic

“…This paper presents a novel method to detect audio copy-move forgery, a type of manipulation where segments of an audio file are duplicated and moved to different locations within the same file. The proposed method consists of two main stages. …”
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Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage by Imad Eddine Toubal, Noor Al-Shakarji, D. D. W. Cornelison, Kannappan Palaniappan

“…Building upon our previous work, we propose a new deep learning-based method, EDNet, for cell detection, tracking, and motility analysis that is more robust to shape across different cell lines, and models cell lineage and proliferation. …”
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A method for intelligent information extraction of coal fractures based on µCT and deep learning by Zhazha HU, Xun ZHANG, Yi JIN, Linxian GONG, Wenhui HUANG, Jianji REN, Norbert Klitzsch

“…First, the µCT images of coal samples were preprocessed, including improving the image quality using the difference method and increasing the sample size using data augmentation techniques. …”
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Enhancing LoRa-Based Outdoor Localization Accuracy Using Machine Learning by Nur Kelesoglu, Marzena Halama, Anna Strzoda

“…Additionally, we investigate the impact of different Feature Vector (FV) subsets on localization performance by analyzing the significance of LoRaWAN signal attributes. …”
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Image-Based Breast Cancer Histopathology Classification and Diagnosis Using Deep Learning Approaches by Lama A. Aldakhil, Haifa F. Alhasson, Shuaa S. Alharbi, Rehan Ullah Khan, Ali Mustafa Qamar

“…This limitation reduces the accuracy of diagnostic results, mainly when applied to different clinical environments. Furthermore, class imbalances within these datasets, where certain cancer types or stages are underrepresented, lead to biased diagnoses, with more common cases being easily identified while rarer cases are frequently missed. …”
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Class-weighted Dempster–Shafer in dual-level fusion for multimodal fake real estate listings detection by Maifuza Mohd Amin, Nor Samsiah Sani, Mohammad Faidzul Nasrudin

“…Single-level fusion models whether at the feature, decision, or intermediate level struggle with balancing the contributions of different modalities leading to suboptimal decision-making. …”
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