A Semi-Supervised Attention Model for Identifying Authentic Sneakers by Yang Yang, Nengjun Zhu, Yifeng Wu, Jian Cao, Dechuan Zhan, Hui Xiong

“…The model draws on the weighted average of the output feature representations, where the weights are determined by an additional shallow neural network. This allows the SSA model to focus on the most important images of a sneaker for use in identification. …”
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Neural ODEs for holographic transport models without translation symmetry by Zhuo-Fan Gu, Yu-Kun Yan, Shao-Feng Wu

“…We convert the flow equation to a Neural Ordinary Differential Equation (Neural ODE), which is a neural network with continuous depth and produces output through a black-box ODE solver. …”
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Prediction of Mine Dust Concentration Based on Grey Markov Model by Zhou Xu, Guo Liwen, Zhang Jiuling, Qin Sijia, Zhu Yi

“…The model was applied to the prediction of mine dust concentration and compared with the prediction results of the BP neural network model, grey prediction model, and ARIMA (1, 2, 1) model. …”
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Modeling the Dynamic Variability of Sub‐Relativistic Outer Radiation Belt Electron Fluxes Using Machine Learning by Donglai Ma, Xiangning Chu, Jacob Bortnik, Seth G. Claudepierre, W. Kent Tobiska, Alfredo Cruz, S. Dave Bouwer, Joseph F. Fennell, J. Bernard Blake

“…Abstract We present a set of neural network models that reproduce the dynamics of electron fluxes in the range of 50 keV ∼1 MeV in the outer radiation belt. …”
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Investigating the Efficiency of Machine Learning Methods for Simulating the Effects of the Paper-Pulp Industry on Aqua Ecosystem Pollution by Mahmoud Ahmadi, Mehran Davallo, Mohsen Jahanshahi, Vahid Kiarostami, Majid Peyravi

“…After that, the efficiency of linear regression, generalized additive model, neural network, and support vector regression for simulating and predicting the trend of MLSS and COD are investigated. …”
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Vortex gust mitigation from onboard measurements using deep reinforcement learning by Brice Martin, Thierry Jardin, Emmanuel Rachelson, Michael Bauerheim

“…The controller is modeled as an artificial neural network, and it is trained to minimize using deep reinforcement learning (DRL). …”
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A guidance to intelligent metamaterials and metamaterials intelligence by Chao Qian, Ido Kaminer, Hongsheng Chen

“…For metamaterials intelligence, we particularly unfold three canonical categories, i.e., wave-based neural network, mathematical operation, and logic operation, all of which directly execute computation, detection, and inference task in physical space. …”
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A study comparing energy consumption and environmental emissions in ostrich meat and egg production by Behrooz Behboodi, Mohammad Gholami Parashkoohi, Davood Mohammad Zamani, Saeed Firouzi

“…This study delves into the impact of egg and meat production on human health, revealing a slight difference of 0.23 disability adjusted life years (DALY), hinting that egg production could potentially have marginally more negative health effects than meat production. Artificial neural network (ANN) analysis indicates that optimizing machinery, diesel fuel, and energy usage can enhance the productivity of meat production. …”
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Predicting the urban water demand by equipping intelligent-based methods with discrete wavelet transform function by Mohammad Reza Alikhani, Ramtin Moeini

“…For this purpose, in this research, artificial intelligence and data mining methods, including genetic programming (GP), gene expression programming (GEP), artificial neural network (ANN), and discrete wavelet transform function, are used to predict the daily drinking water consumption values of WDN. …”
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Evaluating CNN Architectures and Hyperparameter Tuning for Enhanced Lung Cancer Detection Using Transfer Learning by Mohd Munazzer Ansari, Shailendra Kumar, Umair Tariq, Md Belal Bin Heyat, Faijan Akhtar, Mohd Ammar Bin Hayat, Eram Sayeed, Saba Parveen, Dustin Pomary

“…This study evaluates the performance of six convolutional neural network (CNN) architectures, ResNet-50, VGG-16, ResNet-101, VGG-19, DenseNet-201, and EfficientNet-B4, using the LIDC-IDRI dataset. …”
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AI-Enhanced Robotic Process Automation: A Review of Intelligent Automation Innovations by Sadia Afrin, Shobnom Roksana, Riad Akram

“…By leveraging AI techniques such as classification, text mining of neural network, RPA technologies optimize business operations and advance Industry 4.0. …”
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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 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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Sustainable Selection of Machine Learning Algorithm for Gender-Bias Attenuated Prediction by Raik Orbay, Evelina Wikner

“…An investigation into the environmental burden of seven different types of ML algorithms was conducted and the popular neural network algorithm had the highest environmental burden.…”
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Applications of the neuro-evolutionary approach to the parabolic type partial differential equations by Waseem, Asad Ullah, Emad A.A. Ismail, Fuad A. Awwad

“…This work aims to investigate the Cuckoo search-active set algorithm (CS-ASA), which is based on the artificial neural network (ANN) approach to the nonlinear partial differential equations (PDEs). …”
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A Calibration Approach for Elasticity Estimation with Medical Tools by Grube S., Neidhardt M., Hermann A.-K., Sprenger J., Abdolazizi K., Latus S., Cyron C. J., Schlaefer A.

“…Second, we propose to use a more complex material model, e.g., a neural network, that can be trained with the determined elasticities. …”
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A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction by Jini Mol G., Ajith Bosco Raj T.

“…To identify the irregularities in the cardiac data pattern, a gated recurrent unit (GRU) classifier and a one-dimensional convolutional neural network (1D-CNN) are introduced. A typical genetic algorithm (GA) is used to optimize the suggested GRU network in order to pass over the local minima. …”
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Emergency Medical Resources Allocation of Periphery for Epidemic Areas: Based on Infectious Diseases Spatial-Temporal Transmission Path by Xuan Zhao, Benhong Peng, Chaoyu Zheng, Anxia Wan

“…Finally, a graph convolutional neural network (GCN) is conducted to select the supply-side areas for peripheral-epicenter supplies distribution based on information achieved from the bipartite graph. …”
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High-Fidelity Depth Map Reconstruction System With RGB-Guided Super Resolution CNN and Cross-Calibrated Chaos LiDAR by Yu-Chun Ding, Chia-Yu Chang, Pei-Rong Li, Chao-Tsung Huang, Yung-Chen Lin, Tsung Chen, Wei-Lun Lin, Cheng-Ting Lee, Fan-Yi Lin, Yuan-Hao Huang

“…In this work, we propose a depth map reconstruction system that integrates an RGB-guided depth map super-resolution convolutional neural network (CNN) into a stand-alone Chaos LiDAR depth sensor. …”
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Research on TCN Model Based on SSARF Feature Selection in the Field of Human Behavior Recognition by Wei Zhang, Guibo Yu, Shijie Deng

“…To overcome this problem, this paper investigates a temporal convolutional neural network (TCN) model based on improved sparrow search algorithm random forest (SSARF) feature selection to accurately identify human behavioral traits based on wearable devices. …”
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Application of dynamic enhanced scanning with GD-EOB-DTPA MRI based on deep learning algorithm for lesion diagnosis in liver cancer patients by Bo Liu, Jinhua Yang, Yifei Wu, Xi Chen, Xueru Wu

“…Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) technology is in high demand.ObjectivesThe purpose of the study is to segment the liver using an enhanced multi-gradient deep convolution neural network (EMGDCNN) and to identify and categorize a localized liver lesion using a Gd-EOB-DTPA-enhanced MRI.MethodsWe provided the classifier images of the liver in five states (unenhanced, arterial, portal venous, equilibrium, and hepatobiliary) and labeled them with localized liver diseases (hepatocellular carcinoma, metastasis, hemangiomas, cysts, and scarring). …”
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