Influence of Caprock Morphology on Solubility Trapping during CO2 Geological Sequestration by Pradeep Reddy Punnam, Balaji Krishnamurthy, Vikranth Kumar Surasani

“…In the future, the simulation data using Artificial Neural Networks can be applied to predict the structural and solubility trapping of geological formations. …”
Get full text

Feature Guided CNN for Baby’s Facial Expression Recognition by Qing Lin, Ruili He, Peihe Jiang

“…State-of-the-art facial expression methods outperform human beings, especially, thanks to the success of convolutional neural networks (CNNs). However, most of the existing works focus mainly on analyzing an adult’s face and ignore the important problems: how can we recognize facial expression from a baby’s face image and how difficult is it? …”
Get full text

A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution. by Sheng Miao, Guoqing Ni, Guangze Kong, Xiuhe Yuan, Chao Liu, Xiang Shen, Weijun Gao

“…This study explores the application of Three-Dimensional Convolutional Neural Networks (3DCNN) in spatial interpolation to evaluate soil pollution. …”
Get full text

Mathematical and computational modeling for organic and insect frass fertilizer production: A systematic review. by Malontema Katchali, Edward Richard, Henri E Z Tonnang, Chrysantus M Tanga, Dennis Beesigamukama, Kennedy Senagi

“…Mathematical models such as simulation, regression, dynamics, and kinetics have been applied while computational data driven machine learning models such as random forest, support vector machines, gradient boosting, and artificial neural networks have also been applied as well. These models have been used in quantifying nutrients concentration/release, effects of nutrients in agro-production, and fertilizer treatment. …”
Get full text

Image-Based Arabic Sign Language Recognition System Using Transfer Deep Learning Models by Qanita Bani Baker, Nour Alqudah, Tibra Alsmadi, Rasha Awawdeh

“…This study presents an Arabic Sign Language recognition (ArSL) system that utilizes convolutional neural networks (CNNs) and several transfer learning models to automatically and accurately identify Arabic Sign Language characters. …”
Get full text

Enhancing urban air quality prediction using time-based-spatial forecasting framework by Shrikar Jayaraman, Nathezhtha T, Abirami S, Sakthivel G

“…The TBS employs Convolutional Neural Networks (CNNs) to capture spatial dependencies based on normalized latitude and longitude coordinates of the cities. …”
Get full text

Indicator Selection for Topic Popularity Definition Based on AHP and Deep Learning Models by Yuling Hong, Qishan Zhang

“…Through screening the importance of indicators by the deep learning methods such as recurrent neural networks (RNNs), long short-term memory (LSTM), and gated recurrent unit (GRU), a selection model of topic popularity indicators based on AHP is set up. …”
Get full text

Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks by Narun Asvarujanon, Kenji Leibnitz, Naoki Wakamiya, Masayuki Murata

Get full text

Deep Learning Approaches for 3D Model Generation from 2D Artworks to Aid Blind People with Tactile Exploration by Rocco Furferi

“…The survey explores the potentiality of Convolutional Neural Networks, Generative Adversarial Networks, Variational Autoencoders, and zero-shot methods. …”
Get full text

Integrating Machine Learning and Material Feeding Systems for Competitive Advantage in Manufacturing by Müge Sinem Çağlayan, Aslı Aksoy

“…The research employs six machine learning (ML) algorithms—logistic regression (LR), decision trees (DT), random forest (RF), support vector machines (SVM), K-nearest neighbors (K-NN), and artificial neural networks (ANN)—to develop a multi-class classification model for material feeding system selection. …”
Get full text

Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework. by Xiaoyi Zhang, Yakang Zhang, Angelina Lilac Chen, Manning Yu, Lihao Zhang

“…The GNN-TINet utilizes InceptionNet, transformer architectures, and graph neural networks (GNN) to improve precision in multi-label student performance forecasting. …”
Get full text

Data augmentation with occluded facial features for age and gender estimation by Lu En Lin, Chang Hong Lin

“…The effectiveness of our proposed method is verified by implementing the augmentation method and modified cross‐entropy loss on two different convolution neural networks, the slightly modified AdienceNet and the slightly modified VGG16, to perform age and gender classification. …”
Get full text

Deep Transfer Learning for Biology Cross-Domain Image Classification by Chunfeng Guo, Bin Wei, Kun Yu

“…Recently, due to the record-shattering performance, deep convolutional neural networks (DCNNs) have been used more often in biology image classification. …”
Get full text

Double weighted combat data quality evaluation method based on CVF optimized FAHP by Jianwei Wang, Chengsheng Pan, Qing Zhang

“…Analysis of the experimental results indicates that the proposed method reduces the mean squared error to 5.35 when compared to results obtained using FAHP, interval intuitionistic fuzzy methods, and artificial neural networks, bringing it closer to actual standard values. …”
Get full text

A machine learning interpretation of the correlation between poverty and air pollution in the contiguous United States by Sajeev Magesh, Kevin Geng

“…Utilizing linear regression, decision trees, and neural networks, we rigorously examined the data. While the variables were able to predict county-wide poverty rates to reasonably low RMSE and MAE values, our results indicate no significant correlation between poverty levels alone with air pollution indices. …”
Get full text

A Reconfigurable Coarse-to-Fine Approach for the Execution of CNN Inference Models in Low-Power Edge Devices by Auangkun Rangsikunpum, Sam Amiri, Luciano Ost

“…Convolutional neural networks (CNNs) have evolved into essential components for a wide range of embedded applications due to their outstanding efficiency and performance. …”
Get full text

Secured DICOM medical image transition with optimized chaos method for encryption and customized deep learning model for watermarking by R. Abirami, C. Malathy

“…The chaotic encryption technique makes use of the Lorenz map and a Customized Deep Learning Model (CDLM) based on Convolution Neural Networks (CNNs) are presented for watermarking. …”
Get full text

Speech-based personality prediction using deep learning with acoustic and linguistic embeddings by Martin Lukac

“…Using pre-trained convolutional neural networks and transformer-based models, we extracted embeddings representing both acoustic features (e.g., tone, pitch, rhythm) and linguistic content from the speech samples. …”
Get full text

Machine Learning-Driven Scattering Efficiency Prediction in Passive Daytime Radiative Cooling by Changmin Shi, Jiayu Zheng, Ying Wang, Chenjie Gan, Liwen Zhang, Brian W. Sheldon

“…By employing ML models such as linear regression, neural networks, and random forests, we aimed to predict and optimize the scattering efficiency across different pore sizes and mixed-pore-size configurations. …”
Get full text

A high‐capacity and nonvolatile spintronic associative memory hardware accelerator by Mahan Rezaei, Abdolah Amirany, Mohammad Hossein Moaiyeri, Kian Jafari

“…This progress implemented in‐memory‐computing and neural networks, one of today's hottest research topics. …”
Get full text