Formation permeability estimation using mud loss data by deep learning by Yaser Abdollahfard, Seyed Morteza Mirabbasi, Mohammad Ahmadi, Abdolhossein Hemmati-Sarapardeh, Sefatallah Ashoorian

“…This can be used to estimate the formation permeability values. One-dimensional convolutional neural networks(1D-CNN), a type of convolutional neural network, is utilized to be trained with data to perform a regression problem based on the contribution of flattening, dropout, and fully connected layers to estimate permeability with high accuracy (training data R2 = 0.970, testing data R2 = 0.964). …”
Get full text

Joint Detection and Removal of Specular Highlights using Vision Transformer with Multi-scale Patch Attention by Levent Karacan

“…Nevertheless, their presence can adversely affect the efficacy of solutions in various computer vision tasks. Current methodologies typically use Convolutional Neural Network (CNN)-based Unet architectures for specular highlight detection. …”
Get full text

Autonomous Driving Decision-Making Method Based on Spatial-Temporal Fusion Trajectory Prediction by Yutao Luo, Aining Sun, Jiawei Hong

“…Firstly, the spatial interaction between vehicles is implicitly modeled using a graph convolutional neural network and multi-head attention mechanism, and the gated loop unit is embedded to capture the sequential temporal relationship to establish a prediction model incorporating spatial-temporal features. …”
Get full text

AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review by Xuanchi Guo, Yuhan Shao

“…., cone-beam CT, intraoral scanning, and 3D facial images) and deep learning algorithms (e.g., convolutional neural networks) to elucidate the technological breakthroughs in key aspects such as tooth movement trajectory prediction and early detection of root resorption. …”
Get full text

Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm by Pei Shi, Mingjie Tang, Quan Wang, Xiaofei Ma

“…In addition, the traditional Temporal Convolutional Network (TCN) often fails to capture the dynamic fluctuations present in DO data, resulting in suboptimal prediction performance. …”
Get full text

Signal Processing-Free Intelligent Model for Power Quality Disturbances Identification by Mohammed F. Al-Mashdali, Asif Islam, Abdulbasit Hassan, Md Shafiullah, Mujahed Al-Dhaifallah, Khalid Al Fuwail

“…The rise of power quality disturbances (PQD) generates irregularities in voltage and current waveforms, harming smart grid networks and linked devices. …”
Get full text

Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Radiomics features were extracted using Pyradiomics, and deep learning features were derived from convolutional neural network (CNN). Three models were developed: (1) R model: radiomics-based machine learning (ML) algorithms; (2) CNN model: image-based CNN algorithms; (3) DLR model: a hybrid model combining radiomics and deep learning features with ML algorithms. …”
Get full text

WIVIDOSA-Net: Wigner–Ville distribution based obstructive sleep apnea detection using single lead ECG signal by Amit Bhongade, Tapan Kumar Gandhi

“…Then, SWVSs were fed as input to our newly developed DLM named WIgner–VIlle Distribution-based Obstructive Sleep Apnea convolutional neural network (WIVIDOSA-Net) as well as other standard pretrained ResNet-18 and ResNet-50 for comparison. …”
Get full text

Deep-Learning-CNN for Detecting Covered Faces with Niqab by Abdulaziz A. Alashbi, Mohd Shahrizal Sunar, Zieb Alqahtani

Get full text

Robust Simplified Modeling of Microgrid in the Context of Constructing New Power Systems by Daxing WANG, Yan Ning, Jingpei WANG, Yang XU, Jun BI, Mingbiao ZHOU, Peng WANG

“…Next, key parameter selection-based parameter identification method is applied to avoid the issue of multiple solutions in parameter identification process. Then, the convolutional neural network is used to generalize the model parameters with respect to different typical system operation conditions. …”
Get full text

Breast cancer image classification by using HCNN and LeNet5 by Pramoda Patro, Shaik Honey Fathima, R. Harikishore, Aditya Kumar Sahu

“…This model combines a Convolutional Neural Network (CNN) with an Enhanced Recurrent Neural Network (ERNN), leveraging the strengths of both architectures. …”
Get full text

Integrating spatiotemperporal features into fault prediction using a multi-dimensional method by Chun-Yi Lin, Yu-Chuan Tseng, Wu-Sung Yao

“…The short-time Fourier transform is used to convert spatiotemporal data into the frequency domain for classification, and high-order features are extracted through convolutional networks. The model considers three spatial dimensions and three vibration measurement sources to form a nine-dimensional data structure, and a fault prediction algorithm based on these dimensions is established. …”
Get full text

Recognition of Visual Arabic Scripting News Ticker From Broadcast Stream by Moeen Tayyab, Ayyaz Hussain, Mohammed Ali Alshara, Shakir Khan, Reemiah Muneer Alotaibi, Abdul Rauf Baig

Get full text

A review of plant leaf disease identification by deep learning algorithms by Junmin Zhao, Laixiang Xu, Zizhen Ma, Juncai Li, Xiaowei Wang, Yunchang Liu, Xiaojie Du

Get full text

Hybrid TCN-transformer model for predicting sustainable food supply and ensuring resilience by Ibrahim Alrashdi, Rasha M. Abd El-Aziz, Ahmed I. Taloba, Mohammed Farsi

“…Based on the abovementioned limitations, this study proposes a Hybrid TCN-Transformer Model by combining the strength of Temporal Convolutional Networks (TCN) with Transformer Attention to provide accurate and efficient food supply prediction. …”
Get full text

A Predictive Method for Unplanned Postoperative Readmission Risk Based on Heterogeneous Data by Kai YU, Xiaofeng DONG, Zhenming YUAN, Zhaojian CUI, Weibin LUO

Get full text

Facial Beauty Prediction Combining Dual-Branch Feature Fusion With a Stacked Broad Learning System by Junying Gan, Hantian Chen, Wenchao Xu, Huicong Li, Zhenxin Zhuang, Zhen Chen

“…Facial beauty prediction (FBP) is a key computer vision task that uses algorithms to assess facial attractiveness. Current models rely on single feature extraction, such as using a single convolutional neural network to extract local feature, failing to capture other potentially more important information contained within facial data and limiting feature diversity. …”
Get full text

MeetSafe: enhancing robustness against white-box adversarial examples by Ruben Stenhuis, Dazhuang Liu, Yanqi Qiao, Mauro Conti, Manos Panaousis, Kaitai Liang

“…Convolutional neural networks (CNNs) are vulnerable to adversarial attacks in computer vision tasks. …”
Get full text

Exploring spatial reasoning performances of CNN on linear layout dataset by Jelena Pejic, Marko Petkovic, Sandra Klinge

“…To benchmark dataset, we develop LinLayCNN, a generic data-driven method that applies shallow, one-dimensional convolutional neural network (CNN), to generate linear layouts in an iterative process. …”
Get full text

Multi-view Fusion 3D Model Classification by GAO Yuan, DING Bo, HE Yong-jun

Get full text