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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Implementation of the Human-Like Lane Changing Driver Model Based on Bi-LSTM by Junyu Cai, Haobin Jiang, Junyan Wang

“…This paper uses four neural network models to compare the prediction on the test set, then uses different input types to compare the prediction accuracy of the model, and finally verifies the generalization ability of the model on the verification set. …”
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Real-world pharmacovigilance of ofatumumab in multiple sclerosis: a comprehensive FAERS data analysis by Hui Chen

“…Statistical approaches used included the Reporting Odds Ratio, Proportional Reporting Ratio, Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker. …”
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A New Preprocessing Method for Diabetes and Biomedical Data Classification by Sarbast CHALO, İbrahim Berkan AYDİLEK

“…We present a method for the identification of diabetes that involves the training of the features of a deep neural network between five and 10 times using the cross-validation training mode. …”
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Analysis of College Students’ Public Opinion Based on Machine Learning and Evolutionary Algorithm by Jinqing Zhang, Pengchao Zhang, Bin Xu

“…To solve this problem, this paper proposes a new way by using a questionnaire which covers most aspects of a student’s life to collect comprehensive information and feed the information into a neural network. With reliable prediction on students’ state of mind and awareness of feature importance, colleges can give students guidance associated with their own experience and make macroscopic policies more effective. …”
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Unveiling the Complexity of Medical Imaging through Deep Learning Approaches by Javaid Iqbal Bhat, Novsheena Rasool

“…Specifically, an in-depth discussion is conducted on the Convolutional Neural Network (CNN) owing to its widespread adoption as a paramount tool in computer vision tasks. …”
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Evaluation and prediction of coal seam mining mode: Coefficient of Variation-TOPSIS and CNN-NGO methods by Haixiong Li, Fei Wang

“…In addition, a Convolutional Neural Network (CNN) regression model was constructed and optimized with the Northern Goshawk Optimization (NGO) algorithm, resulting in a more precise CNN-NGO prediction model. …”
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Evaluation of Efficacy of Artificial Intelligence in Orthopantomogram in Detecting and Classifying Radiolucent Lesions by Sheetal Singar, Ajay Parihar, Prashanthi Reddy

“…Aim and Objective: The objective of our study was to build a convolutional neural network (CNN) model and detection and classification of benign and malignant radiolucent lesions in orthopantomogram (OPG) by implementing CNN. …”
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A Small Target Detection Method Based on the Improved FCN Model by Guofeng Ma

“…This study proposes an improved FCN model based on the full convolutional neural network (FCN) and applies it to the STD. The following is the central concept of the proposed method. …”
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Robust identification method of website fingerprinting against disturbance by ZHANG Jingxi, LI Tengyao, TU Yukuan, LUO Xiangyang

“…With the matrix as input, a robust flow classifier with convolutional neural network was established. Through extensive experimental analysis on the dataset provided by DF, the accuracy under RF Countermeasure is 95.4%, which is 21.2% higher than RF. …”
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Features of the restaurant market and consumer behavior in the Moscow restaurant business segment: study results by A. N. Timokhovich

“…At the second stage to identify the main trends of the Moscow restaurant market the method of content analysis of the Moscow restaurant business establishments sites with high rating indicators based on the Yandex neural network data was used. The main trends of the Moscow restaurant market are: restaurants’ focus on preparing healthy food and vegetarian cuisine; use of farm products and local ingredients in prepared dishes; technological innovations implementation that simplify consumer experience; focus on the principles of sustainable development and environmental friendliness in the business model; restaurant formats variety. …”
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Robust CNN for facial emotion recognition and real-time GUI by Imad Ali, Faisal Ghaffar

“…Utilizing a robust architecture of a convolutional neural network (CNN), we designed an efficacious framework for facial emotion recognition that predicts emotions and assigns corresponding probabilities to each fundamental human emotion. …”
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Hyperbolic Graph Convolutional Network Relation Extraction Model Combining Dependency Syntax and Contrastive Learning by Jinzhe Li

“…Based on the hyperbolic graph neural network, dependent syntactic information and information optimization strategies are introduced to solve the problem of word embedding concentration. …”
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On the Analysis and Assessment of First-Order Group Contribution Models for the Calculation of Normal Boiling Point and Critical Properties of Pure Compounds by Vanessa Villazón-León, Adrián Bonilla-Petriciolet, Juan Carlos Tapia-Picazo

“…The performance of these models was characterized and compared for several compound families using a standardized approach to determine their group contributions and parameters. An artificial neural network model was also applied and assessed to improve the estimations obtained with the best group contribution models. …”
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Enhancing Image-Based JPEG Compression: ML-Driven Quantization via DCT Feature Clustering by Shahrzad Sabzavi, Reza Ghaderi

“…In this study, an auto-encoder neural network is utilized to extract DCT features from images. …”
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The Reduced-Order Model for Droplet Drift of Aerial Spraying under Random Lateral Wind by Wencheng Li, Wenyun Wang, Xiaomao Huang, Chenyang Li

“…Based on the input and output dataset of CFD, the recursive algorithm including nonlinear autoregressive exogenous model and surrogate-based recurrence framework and the deep learning method for time-series prediction called long short-term memory neural network are used to build the efficient reduced-order model, respectively. …”
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End-to-End Semantic Leaf Segmentation Framework for Plants Disease Classification by Khalil Khan, Rehan Ullah Khan, Waleed Albattah, Ali Mustafa Qamar

“…Our model uses a deep convolutional neural network based on semantic segmentation (SS). The proposed algorithm highlights diseased and healthy parts and allows the classification of ten different diseases affecting a specific plant leaf. …”
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Static Mechanical Properties and Microscopic Analysis of Hybrid Fiber Reinforced Ultra-High Performance Concrete with Coarse Aggregate by Shengbing Liu, Yonglei Zhang

“…Finally, three kinds of strength parameters are predicted based on the back propagation (BP) neural network system. The absolute value of the relative error between the predicted strength and the experimental value is less than 5%, which indicates that the prediction model proposed in this paper can provide a reference for the multiobjective optimization of the mix proportion of hybrid fiber ultra-high performance concrete.…”
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Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models. by Zenglei Liu, Ailian Gao, Hui Sheng, Xueling Wang

“…Considering these analyses, this work presents a comprehensive deep learning model that combines convolutional neural network and vision mamba models. This model is designed to accurately identify and classify diabetic retinopathy lesions displayed in fundus images. …”
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