Assessing land degradation in lower gangetic west bengal using GIS-based soft computing and advanced machine learning algorithms by Gopal Chowdhury, Ashis Kumar Saha

“…Two advanced machine learning models were used: the Multilayer Perceptron Neural Network (MLP-NN) and the Radial Basis Function Neural Network (RBF-NN). …”
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Deep learning-driven 3D marine nitrate estimation: uncertainty mitigation through underwater signal exploitation and label augmentation by Xiang Yu, Guodong Fan, Jinjiang Li

“…The proposed uncertainty-weighted loss function refines model training, balancing the quality and training impact of both observed and augmented labels. …”
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A dictionary learning approach with overlap for the low dose computed tomography reconstruction and its vectorial application to differential phase tomography. by Alessandro Mirone, Emmanuel Brun, Paola Coan

“…In this scenario, we implemented a dictionary learning method with a new form of convex functional. …”
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Attention Mechanism with Spatial-Temporal Joint Deep Learning Model for the Forecasting of Short-Term Passenger Flow Distribution at the Railway Station by Zhicheng Dai, Dewei Li, Shiqing Feng

“…Emerging deep learning models offer valuable insights for accurately predicting passenger flow distribution. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…This study integrated hyperspectral technology with machine learning algorithms to model complex nonlinear relationships and to select the optimal SWHC model. …”
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A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study by Jing Xu, Wenjin Zhang, Wenli Liu

“…Depression was assessed with the CESD-10 scale. Three machine learning models—Gradient Boosting, Random Forest, and Boosted XGBoost—were used to predict depression risk over three years, incorporating 10 demographic, 5 health, 13 chronic disease, 3 lifestyle, and 2 physical function factors. …”
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Evaluation of Parametric and Non-Parametric Models in Estimating Canopy Cover Density of Zagros Forests Using Remote Sensing and Machine Learning by Sajad Alimahmoodi Sarab, MohamadHadi Moayery, MOhammad Mirzavand, Shaban Shataee Jouibary, Alireza Rashki

“…Subsequently, the values derived from the vegetation cover indices at the sample plots were extracted using the Zonal Statistics function in ArcGIS. Multiple linear regression and artificial neural networks were employed to estimate vegetation density. …”
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Safety–Efficiency Balanced Navigation for Unmanned Tracked Vehicles in Uneven Terrain Using Prior-Based Ensemble Deep Reinforcement Learning by Yiming Xu, Songhai Zhu, Dianhao Zhang, Yinda Fang, Mien Van

“…This paper proposes a novel navigation approach for Unmanned Tracked Vehicles (UTVs) using prior-based ensemble deep reinforcement learning, which fuses the policy of the ensemble Deep Reinforcement Learning (DRL) and Dynamic Window Approach (DWA) to enhance both exploration efficiency and deployment safety in unstructured off-road environments. …”
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Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran by Mahnoosh Moghaddasi, Mansour Moradi, Mahdi Mohammadi Ghaleni, Zaher Mundher Yaseen

“…Key parameters of the DFFNN, including the number of neurons and layers, learning rate, training function, and weight initialization, were optimized using the WSO algorithm. …”
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A Machine Learning and Remote Sensing‐Based Model for Algae Pigment and Dissolved Oxygen Retrieval on a Small Inland Lake by Maxwell R. W. Beal, Mutlu Özdoğan, Paul J. Block

“…Abstract Excessive algae growth can lead to negative consequences for ecosystem function, economic opportunity, and human and animal health. …”
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VariGAN: Enhancing Image Style Transfer via UNet Generator, Depthwise Discriminator, and LPIPS Loss in Adversarial Learning Framework by Dawei Guan, Xinping Lin, Haoyi Zhang, Hang Zhou

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Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…At the same time, based on the convolutional neural network model Alexnet, the cross-entropy loss function is selected as the training loss, and the twisted tire porcelain pattern classification algorithm under the deep learning framework is designed. …”
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Multi-heat keypoint incorporation in deep learning model to tropical cyclone centering and intensity classifying from geostationary satellite images by Thanh-Ha Do, Son-The Phan, Duc-Tien Du, Dinh-Quan Dang, Khanh-Hung Mai, Lars R. Hole

“…This paper proposes a new multitask deep learning model with attention gate mechanisms to work with satellite images and construct heatmaps for TC’s centering and classification. …”
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Robot-assisted axillary lymph node dissection in patients with node-positive breast cancer: techniques, learning curve, and preliminary results by Zhjie Wu, Zuxiao Chen, Zongyan Li, Xiaoyan Fu, Yunxiang Luo, Qiongyu Hu, Haiyan Li

“…The clinicopathological characteristics, learning curve, and consequences of RALND were investigated to determine the efficacy and safety of RALND. …”
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ResGRU: A Novel Hybrid Deep Learning Model for Compound Fault Diagnosis in Photovoltaic Arrays Considering Dust Impact by Xi Liu, Hui Hwang Goh, Haonan Xie, Tingting He, Weng Kean Yew, Dongdong Zhang, Wei Dai, Tonni Agustiono Kurniawan

“…To further optimize inter-class separability and intra-class compactness, a center loss function is employed as an auxiliary loss to enhance the model’s discriminative capacity. …”
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Multi-scale attention-enhanced deep learning approach for detecting seven trunk pests and diseases in Shanghai’s urban plane trees by Tianyang Song, Guohua Hu, Tianci Yu, Xing Meng, Yanting Zhang, Ruiqing Yang, Benyao Wang, Xia Li

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JASBO: Jaya Average Subtraction Based Optimization with Deep Learning Model for Multi-Classification of Infectious Disease from Unstructured Data by Vian Sabeeh, Ahmed Bahaaulddin A. Alwahhab, Ali Abdulmunim Ibrahim Al-kharaz

“…Character level features are passed to the attention layer, which uses the Kumar-Hassebrook similarity measure to calculate the score function. Label of each word token is then predicted by the ID layer, at which layer size is found by JASBO. …”
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Neurocognition as a major predictor of 8-week response to antipsychotics for drug-naïve first-episode schizophrenia using machine learning by Xianghe Wang, Tianqi Gao, Xiaodong Guo, Bingjie Huang, Yunfei Ji, Wanheng Hu, Xiaolin Yin, Yue Zheng, Chengcheng Pu, Xin Yu

“…The current study aimed to build a prediction model of eight-week antipsychotic response based on baseline clinical and demographic features. Six machine learning algorithms, including random forest, eXtreme gradient boosting (XGBoost), logistic regression, linear support vector machine (SVM), radial basis function SVM and poly SVM were applied and compared to draw the prediction model. …”
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CLPM: A Hybrid Network With Cross-Space Learning and Perception-Driven Mechanism for Long-Tailed Remote Sensing Image Classification by Lei Zhang, Min Kong, Changfeng Jing, Xing Xing

“…Building on this, a vMF-based contrastive loss function is proposed. This approach effectively coordinates the learning processes of head and tail classes while enhancing the precision of feature representation. …”
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Effect of a Novel Training Program in Patients With Chronic Shoulder Pain Based on Implicit Motor Learning: Pilot and Feasibility Study. by Annelies Maenhout, Wieger Heijenk, Peter Glashouwer, Lore Quatacker, Luna Praet, Dorien Borms

“…# Background Implicit motor learning has been shown to be effective for learning sports-related motor skills. …”
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